Cross-domain active learning for video concept detection

NASA Astrophysics Data System (ADS)

Li, Huan; Li, Chao; Shi, Yuan; Xiong, Zhang; Hauptmann, Alexander G.

2011-08-01

As video data from a variety of different domains (e.g., news, documentaries, entertainment) have distinctive data distributions, cross-domain video concept detection becomes an important task, in which one can reuse the labeled data of one domain to benefit the learning task in another domain with insufficient labeled data. In this paper, we approach this problem by proposing a cross-domain active learning method which iteratively queries labels of the most informative samples in the target domain. Traditional active learning assumes that the training (source domain) and test data (target domain) are from the same distribution. However, it may fail when the two domains have different distributions because querying informative samples according to a base learner that initially learned from source domain may no longer be helpful for the target domain. In our paper, we use the Gaussian random field model as the base learner which has the advantage of exploring the distributions in both domains, and adopt uncertainty sampling as the query strategy. Additionally, we present an instance weighting trick to accelerate the adaptability of the base learner, and develop an efficient model updating method which can significantly speed up the active learning process. Experimental results on TRECVID collections highlight the effectiveness.

Multi-Domain Transfer Learning for Early Diagnosis of Alzheimer's Disease.

PubMed

Cheng, Bo; Liu, Mingxia; Shen, Dinggang; Li, Zuoyong; Zhang, Daoqiang

2017-04-01

Recently, transfer learning has been successfully applied in early diagnosis of Alzheimer's Disease (AD) based on multi-domain data. However, most of existing methods only use data from a single auxiliary domain, and thus cannot utilize the intrinsic useful correlation information from multiple domains. Accordingly, in this paper, we consider the joint learning of tasks in multi-auxiliary domains and the target domain, and propose a novel Multi-Domain Transfer Learning (MDTL) framework for early diagnosis of AD. Specifically, the proposed MDTL framework consists of two key components: 1) a multi-domain transfer feature selection (MDTFS) model that selects the most informative feature subset from multi-domain data, and 2) a multi-domain transfer classification (MDTC) model that can identify disease status for early AD detection. We evaluate our method on 807 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database using baseline magnetic resonance imaging (MRI) data. The experimental results show that the proposed MDTL method can effectively utilize multi-auxiliary domain data for improving the learning performance in the target domain, compared with several state-of-the-art methods.

38 CFR 21.9625 - Beginning dates.

Code of Federal Regulations, 2011 CFR

2011-07-01

...) Entrance or reentrance including change of program or institution of higher learning. When an eligible... institution of higher learning), the beginning date of his or her award of educational assistance will be... education, the beginning date will be the latest of— (A) The date the institution of higher learning...

Current Heavy Alcohol Consumption is Associated with Greater Cognitive Impairment in Older Adults

PubMed Central

Woods, Adam J.; Porges, Eric C.; Bryant, Vaughn E.; Seider, Talia; Gongvatana, Assawin; Kahler, Christopher W.; de la Monte, Suzanne; Monti, Peter M.; Cohen, Ronald A.

2016-01-01

Background The acute consumption of excessive quantities of alcohol causes well-recognized neurophysiological and cognitive alterations. As people reach advanced age, they are more prone to cognitive decline. To date, the interaction of current heavy alcohol (ETOH) consumption and aging remain unclear. The current paper tested the hypothesis that negative consequences of current heavy alcohol consumption on neurocognitive function are worse with advanced age. Further, we evaluated the relations between lifetime history of alcohol dependence and neurocognitive function Methods Sixty-six participants underwent a comprehensive neurocognitive battery. Current heavy ETOH drinkers were classified using NIAAA criteria (ETOH Heavy, n = 21) based on the Timeline follow-back and a structured clinical interview and compared to non-drinkers, and moderate drinkers (ETOH Low, n = 45). Fifty-three-point-three percent of the total population had a lifetime history of alcohol dependence. Neurocognitive data were grouped and analyzed relative to global and domain scores assessing: global cognitive function, attention/executive function, learning, memory, motor function, verbal function, and speed of processing. Results Heavy current ETOH consumption in older adults was associated with poorer global cognitive function, learning, memory, and motor function (p’s<.05). Furthermore, lifetime history of alcohol dependence was associated with poorer function in the same neurocognitive domains, in addition to the attention/executive domain, irrespective of age (p’s<.05). Conclusions These data suggest that while heavy current alcohol consumption is associated with significant impairment in a number of neurocognitive domains, history of alcohol dependence, even in the absence of heavy current alcohol use, is associated with lasting negative consequences for neurocognitive function. PMID:27658235

Domain-specific learning of grammatical structure in musical and phonological sequences.

PubMed

Bly, Benjamin Martin; Carrión, Ricardo E; Rasch, Björn

2009-01-01

Artificial grammar learning depends on acquisition of abstract structural representations rather than domain-specific representational constraints, or so many studies tell us. Using an artificial grammar task, we compared learning performance in two stimulus domains in which respondents have differing tacit prior knowledge. We found that despite grammatically identical sequence structures, learning was better for harmonically related chord sequences than for letter name sequences or harmonically unrelated chord sequences. We also found transfer effects within the musical and letter name tasks, but not across the domains. We conclude that knowledge acquired in implicit learning depends not only on abstract features of structured stimuli, but that the learning of regularities is in some respects domain-specific and strongly linked to particular features of the stimulus domain.

Building adaptive capacity to climate change in tropical coastal communities

NASA Astrophysics Data System (ADS)

Cinner, Joshua E.; Adger, W. Neil; Allison, Edward H.; Barnes, Michele L.; Brown, Katrina; Cohen, Philippa J.; Gelcich, Stefan; Hicks, Christina C.; Hughes, Terry P.; Lau, Jacqueline; Marshall, Nadine A.; Morrison, Tiffany H.

2018-01-01

To minimize the impacts of climate change on human wellbeing, governments, development agencies, and civil society organizations have made substantial investments in improving people's capacity to adapt to change. Yet to date, these investments have tended to focus on a very narrow understanding of adaptive capacity. Here, we propose an approach to build adaptive capacity across five domains: the assets that people can draw upon in times of need; the flexibility to change strategies; the ability to organize and act collectively; learning to recognize and respond to change; and the agency to determine whether to change or not.

Multi-Domain Transfer Learning for Early Diagnosis of Alzheimer’s Disease

PubMed Central

Cheng, Bo; Liu, Mingxia; Li, Zuoyong

2017-01-01

Recently, transfer learning has been successfully applied in early diagnosis of Alzheimer’s Disease (AD) based on multi-domain data. However, most of existing methods only use data from a single auxiliary domain, and thus cannot utilize the intrinsic useful correlation information from multiple domains. Accordingly, in this paper, we consider the joint learning of tasks in multi-auxiliary domains and the target domain, and propose a novel Multi-Domain Transfer Learning (MDTL) framework for early diagnosis of AD. Specifically, the proposed MDTL framework consists of two key components: 1) a multi-domain transfer feature selection (MDTFS) model that selects the most informative feature subset from multi-domain data, and 2) a multidomain transfer classification (MDTC) model that can identify disease status for early AD detection. We evaluate our method on 807 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database using baseline magnetic resonance imaging (MRI) data. The experimental results show that the proposed MDTL method can effectively utilize multi-auxiliary domain data for improving the learning performance in the target domain, compared with several state-of-the-art methods. PMID:27928657

Identity, Intimacy, Status and Sex Dating Goals as Correlates of Goal-Consistent Behavior and Satisfaction in Australian Youth

ERIC Educational Resources Information Center

Kelly, Marguerite; Zimmer-Gembeck, Melanie J.; Boislard-P., Marie-Aude

2012-01-01

The most common dating goals of adolescents are identity, intimacy, status and sex. In this study of Australian youth (16-30 years, N = 208), dating goals were expected to explain goal-consistent behavior in each domain. Also, goals coupled with consistent behavior were expected to be associated with greater satisfaction in each domain. Age,…

Randomized Trial of Reducing Ambulatory Malpractice and Safety Risk: Results of the Massachusetts PROMISES Project.

PubMed

Schiff, Gordon D; Reyes Nieva, Harry; Griswold, Paula; Leydon, Nicholas; Ling, Judy; Federico, Frank; Keohane, Carol; Ellis, Bonnie R; Foskett, Cathy; Orav, E John; Yoon, Catherine; Goldmann, Don; Weissman, Joel S; Bates, David W; Biondolillo, Madeleine; Singer, Sara J

2017-08-01

Evaluate application of quality improvement approaches to key ambulatory malpractice risk and safety areas. In total, 25 small-to-medium-sized primary care practices (16 intervention; 9 control) in Massachusetts. Controlled trial of a 15-month intervention including exposure to a learning network, webinars, face-to-face meetings, and coaching by improvement advisors targeting "3+1" high-risk domains: test result, referral, and medication management plus culture/communication issues evaluated by survey and chart review tools. Chart reviews conducted at baseline and postintervention for intervention sites. Staff and patient survey data collected at baseline and postintervention for intervention and control sites. Chart reviews demonstrated significant improvements in documentation of abnormal results, patient notification, documentation of an action or treatment plan, and evidence of a completed plan (all P<0.001). Mean days between laboratory test date and evidence of completed action/treatment plan decreased by 19.4 days (P<0.001). Staff surveys showed modest but nonsignificant improvement for intervention practices relative to controls overall and for the 3 high-risk domains that were the focus of PROMISES. A consortium of stakeholders, quality improvement tools, coaches, and learning network decreased selected ambulatory safety risks often seen in malpractice claims.

Approaches to Learning and School Readiness in Head Start: Applications to Preschool Science

ERIC Educational Resources Information Center

Bustamante, Andres S.; White, Lisa J.; Greenfield, Daryl B.

2017-01-01

Approaches to learning are a set of domain-general skills that encompass curiosity, persistence, planning, and engagement in group learning. These skills play a key role in preschoolers' learning and predict school readiness in math and language. Preschool science is a critical domain for early education and facilitates learning across domains.…

Domain adaptation via transfer component analysis.

PubMed

Pan, Sinno Jialin; Tsang, Ivor W; Kwok, James T; Yang, Qiang

2011-02-01

Domain adaptation allows knowledge from a source domain to be transferred to a different but related target domain. Intuitively, discovering a good feature representation across domains is crucial. In this paper, we first propose to find such a representation through a new learning method, transfer component analysis (TCA), for domain adaptation. TCA tries to learn some transfer components across domains in a reproducing kernel Hilbert space using maximum mean miscrepancy. In the subspace spanned by these transfer components, data properties are preserved and data distributions in different domains are close to each other. As a result, with the new representations in this subspace, we can apply standard machine learning methods to train classifiers or regression models in the source domain for use in the target domain. Furthermore, in order to uncover the knowledge hidden in the relations between the data labels from the source and target domains, we extend TCA in a semisupervised learning setting, which encodes label information into transfer components learning. We call this extension semisupervised TCA. The main contribution of our work is that we propose a novel dimensionality reduction framework for reducing the distance between domains in a latent space for domain adaptation. We propose both unsupervised and semisupervised feature extraction approaches, which can dramatically reduce the distance between domain distributions by projecting data onto the learned transfer components. Finally, our approach can handle large datasets and naturally lead to out-of-sample generalization. The effectiveness and efficiency of our approach are verified by experiments on five toy datasets and two real-world applications: cross-domain indoor WiFi localization and cross-domain text classification.

Rehabilitation of Poststroke Cognition

PubMed Central

Shigaki, Cheryl L.; Frey, Scott H.; Barrett, A.M.

2015-01-01

Given the increasing rates of stroke and our aging population, it is critical that we continue to foster innovation in stroke rehabilitation. Although there is evidence supporting cognitive rehabilitation in stroke, the set of cognitive domains effectively addressed to date represents only a small subset of the problems experienced by stroke survivors. Further, a gap remains between investigational treatments and our evolving theories of brain function. These limitations present opportunities for improving the functional impact of stroke rehabilitation. The authors use a case example to encourage the reader to consider the evidence base for cognitive rehabilitation in stroke, focusing on four domains critical to daily life function: (1) speech and language, (2) functional memory, (3) executive function and skilled learned purposive movements, and (4) spatial-motor systems. Ultimately, they attempt to draw neuroscience and practice closer together by using translational reasoning to suggest possible new avenues for treating these disorders. PMID:25520021

Economic decision-making in the ultimatum game by smokers.

PubMed

Takahashi, Taiki

2007-10-01

No study to date compared degrees of inequity aversion in economic decision-making in the ultimatum game between non-addictive and addictive reinforcers. The comparison is potentially important in neuroeconomics and reinforcement learning theory of addiction. We compared the degrees of inequity aversion in the ultimatum game between money and cigarettes in habitual smokers. Smokers avoided inequity in the ultimatum game more dramatically for money than for cigarettes; i.e., there was a "domain effect" in decision-making in the ultimatum game. Reward-processing neural activities in the brain for non-addictive and addictive reinforcers may be distinct and the insula activation due to cue-induced craving may conflict with unfair offer-induced insula activation. Future studies in neuroeconomics of addiction should employ game-theoretic decision tasks for elucidating reinforcement learning processes in dopaminergic neural circuits.

Comparison of learning models based on mathematics logical intelligence in affective domain

NASA Astrophysics Data System (ADS)

Widayanto, Arif; Pratiwi, Hasih; Mardiyana

2018-04-01

The purpose of this study was to examine the presence or absence of different effects of multiple treatments (used learning models and logical-mathematical intelligence) on the dependent variable (affective domain of mathematics). This research was quasi experimental using 3x3 of factorial design. The population of this research was VIII grade students of junior high school in Karanganyar under the academic year 2017/2018. Data collected in this research was analyzed by two ways analysis of variance with unequal cells using 5% of significance level. The result of the research were as follows: (1) Teaching and learning with model TS lead to better achievement in affective domain than QSH, teaching and learning with model QSH lead to better achievement in affective domain than using DI; (2) Students with high mathematics logical intelligence have better achievement in affective domain than students with low mathematics logical intelligence have; (3) In teaching and learning mathematics using learning model TS, students with moderate mathematics logical intelligence have better achievement in affective domain than using DI; and (4) In teaching and learning mathematics using learning model TS, students with low mathematics logical intelligence have better achievement in affective domain than using QSH and DI.

Efficient learning mechanisms hold in the social domain and are implemented in the medial prefrontal cortex

PubMed Central

Tobler, Philippe N.

2015-01-01

When we are learning to associate novel cues with outcomes, learning is more efficient if we take advantage of previously learned associations and thereby avoid redundant learning. The blocking effect represents this sort of efficiency mechanism and refers to the phenomenon in which a novel stimulus is blocked from learning when it is associated with a fully predicted outcome. Although there is sufficient evidence that this effect manifests itself when individuals learn about their own rewards, it remains unclear whether it also does when they learn about others’ rewards. We employed behavioral and neuroimaging methods to address this question. We demonstrate that blocking does indeed occur in the social domain and it does so to a similar degree as observed in the individual domain. On the neural level, activations in the medial prefrontal cortex (mPFC) show a specific contribution to blocking and learning-related prediction errors in the social domain. These findings suggest that the efficiency principle that applies to reward learning in the individual domain also applies to that in the social domain, with the mPFC playing a central role in implementing it. PMID:25326037

U.S. stock market interaction network as learned by the Boltzmann machine

DOE PAGES

Borysov, Stanislav S.; Roudi, Yasser; Balatsky, Alexander V.

2015-12-07

Here, we study historical dynamics of joint equilibrium distribution of stock returns in the U.S. stock market using the Boltzmann distribution model being parametrized by external fields and pairwise couplings. Within Boltzmann learning framework for statistical inference, we analyze historical behavior of the parameters inferred using exact and approximate learning algorithms. Since the model and inference methods require use of binary variables, effect of this mapping of continuous returns to the discrete domain is studied. The presented results show that binarization preserves the correlation structure of the market. Properties of distributions of external fields and couplings as well as themore » market interaction network and industry sector clustering structure are studied for different historical dates and moving window sizes. We demonstrate that the observed positive heavy tail in distribution of couplings is related to the sparse clustering structure of the market. We also show that discrepancies between the model’s parameters might be used as a precursor of financial instabilities.« less

Collaboration Technology in Military Operations: Lessons Learned from the Corporate Domain

DTIC Science & Technology

2006-02-01

Learned from the Corporate Domain Topics: Social Domain Issues, Cognitive Domain Issues, C2 Experimentation Authors: Stacey D. Scott, M. L. Cummings, David...AFRL-HE-WP-TP-2006-0029 AIR FORCE RESEARCH LABORATORY Collaboration Technology in Military Operations: Lessons Learned from the Corporate Domain...OMB No. 0704-0188 Public reporting burden for this collection of information is estimated to average 1 hour per response , including the time for

38 CFR 21.9635 - Discontinuance dates.

Code of Federal Regulations, 2013 CFR

2013-07-01

... effective the last date of attendance; and (ii) Independent study or distance learning effective on the... learning, VA will terminate educational assistance effective the date the last lesson was serviced... Discontinuance dates. The effective date of a reduction or discontinuance of educational assistance will be as...

Recent developments in learning control and system identification for robots and structures

NASA Technical Reports Server (NTRS)

Phan, M.; Juang, J.-N.; Longman, R. W.

1990-01-01

This paper reviews recent results in learning control and learning system identification, with particular emphasis on discrete-time formulation, and their relation to adaptive theory. Related continuous-time results are also discussed. Among the topics presented are proportional, derivative, and integral learning controllers, time-domain formulation of discrete learning algorithms. Newly developed techniques are described including the concept of the repetition domain, and the repetition domain formulation of learning control by linear feedback, model reference learning control, indirect learning control with parameter estimation, as well as related basic concepts, recursive and non-recursive methods for learning identification.

Efficient learning mechanisms hold in the social domain and are implemented in the medial prefrontal cortex.

PubMed

Seid-Fatemi, Azade; Tobler, Philippe N

2015-05-01

When we are learning to associate novel cues with outcomes, learning is more efficient if we take advantage of previously learned associations and thereby avoid redundant learning. The blocking effect represents this sort of efficiency mechanism and refers to the phenomenon in which a novel stimulus is blocked from learning when it is associated with a fully predicted outcome. Although there is sufficient evidence that this effect manifests itself when individuals learn about their own rewards, it remains unclear whether it also does when they learn about others' rewards. We employed behavioral and neuroimaging methods to address this question. We demonstrate that blocking does indeed occur in the social domain and it does so to a similar degree as observed in the individual domain. On the neural level, activations in the medial prefrontal cortex (mPFC) show a specific contribution to blocking and learning-related prediction errors in the social domain. These findings suggest that the efficiency principle that applies to reward learning in the individual domain also applies to that in the social domain, with the mPFC playing a central role in implementing it. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Content validation of an interprofessional learning video peer assessment tool.

PubMed

Nisbet, Gillian; Jorm, Christine; Roberts, Chris; Gordon, Christopher J; Chen, Timothy F

2017-12-16

Large scale models of interprofessional learning (IPL) where outcomes are assessed are rare within health professional curricula. To date, there is sparse research describing robust assessment strategies to support such activities. We describe the development of an IPL assessment task based on peer rating of a student generated video evidencing collaborative interprofessional practice. We provide content validation evidence of an assessment rubric in the context of large scale IPL. Two established approaches to scale development in an educational setting were combined. A literature review was undertaken to develop a conceptual model of the relevant domains and issues pertaining to assessment of student generated videos within IPL. Starting with a prototype rubric developed from the literature, a series of staff and student workshops were undertaken to integrate expert opinion and user perspectives. Participants assessed five-minute videos produced in a prior pilot IPL activity. Outcomes from each workshop informed the next version of the rubric until agreement was reached on anchoring statements and criteria. At this point the rubric was declared fit to be used in the upcoming mandatory large scale IPL activity. The assessment rubric consisted of four domains: patient issues, interprofessional negotiation; interprofessional management plan in action; and effective use of video medium to engage audience. The first three domains reflected topic content relevant to the underlying construct of interprofessional collaborative practice. The fourth domain was consistent with the broader video assessment literature calling for greater emphasis on creativity in education. We have provided evidence for the content validity of a video-based peer assessment task portraying interprofessional collaborative practice in the context of large-scale IPL activities for healthcare professional students. Further research is needed to establish the reliability of such a scale.

Domain generality vs. modality specificity: The paradox of statistical learning

PubMed Central

Frost, Ram; Armstrong, Blair C.; Siegelman, Noam; Christiansen, Morten H.

2015-01-01

Statistical learning is typically considered to be a domain-general mechanism by which cognitive systems discover the underlying distributional properties of the input. Recent studies examining whether there are commonalities in the learning of distributional information across different domains or modalities consistently reveal, however, modality and stimulus specificity. An important question is, therefore, how and why a hypothesized domain-general learning mechanism systematically produces such effects. We offer a theoretical framework according to which statistical learning is not a unitary mechanism, but a set of domain-general computational principles, that operate in different modalities and therefore are subject to the specific constraints characteristic of their respective brain regions. This framework offers testable predictions and we discuss its computational and neurobiological plausibility. PMID:25631249

Self-Taught Low-Rank Coding for Visual Learning.

PubMed

Li, Sheng; Li, Kang; Fu, Yun

2018-03-01

The lack of labeled data presents a common challenge in many computer vision and machine learning tasks. Semisupervised learning and transfer learning methods have been developed to tackle this challenge by utilizing auxiliary samples from the same domain or from a different domain, respectively. Self-taught learning, which is a special type of transfer learning, has fewer restrictions on the choice of auxiliary data. It has shown promising performance in visual learning. However, existing self-taught learning methods usually ignore the structure information in data. In this paper, we focus on building a self-taught coding framework, which can effectively utilize the rich low-level pattern information abstracted from the auxiliary domain, in order to characterize the high-level structural information in the target domain. By leveraging a high quality dictionary learned across auxiliary and target domains, the proposed approach learns expressive codings for the samples in the target domain. Since many types of visual data have been proven to contain subspace structures, a low-rank constraint is introduced into the coding objective to better characterize the structure of the given target set. The proposed representation learning framework is called self-taught low-rank (S-Low) coding, which can be formulated as a nonconvex rank-minimization and dictionary learning problem. We devise an efficient majorization-minimization augmented Lagrange multiplier algorithm to solve it. Based on the proposed S-Low coding mechanism, both unsupervised and supervised visual learning algorithms are derived. Extensive experiments on five benchmark data sets demonstrate the effectiveness of our approach.

Finding accurate frontiers: A knowledge-intensive approach to relational learning

NASA Technical Reports Server (NTRS)

Pazzani, Michael; Brunk, Clifford

1994-01-01

An approach to analytic learning is described that searches for accurate entailments of a Horn Clause domain theory. A hill-climbing search, guided by an information based evaluation function, is performed by applying a set of operators that derive frontiers from domain theories. The analytic learning system is one component of a multi-strategy relational learning system. We compare the accuracy of concepts learned with this analytic strategy to concepts learned with an analytic strategy that operationalizes the domain theory.

38 CFR 21.9625 - Beginning dates.

Code of Federal Regulations, 2014 CFR

2014-07-01

... of higher learning certifies under paragraph (b) or (c) of this section; (B) The effective date of...) Entrance or reentrance including change of program or institution of higher learning. When an eligible... institution of higher learning), the beginning date of his or her award of educational assistance will be...

38 CFR 21.9625 - Beginning dates.

Code of Federal Regulations, 2013 CFR

2013-07-01

... of higher learning certifies under paragraph (b) or (c) of this section; (B) The effective date of...) Entrance or reentrance including change of program or institution of higher learning. When an eligible... institution of higher learning), the beginning date of his or her award of educational assistance will be...

Value-driven attentional capture in the auditory domain.

PubMed

Anderson, Brian A

2016-01-01

It is now well established that the visual attention system is shaped by reward learning. When visual features are associated with a reward outcome, they acquire high priority and can automatically capture visual attention. To date, evidence for value-driven attentional capture has been limited entirely to the visual system. In the present study, I demonstrate that previously reward-associated sounds also capture attention, interfering more strongly with the performance of a visual task. This finding suggests that value-driven attention reflects a broad principle of information processing that can be extended to other sensory modalities and that value-driven attention can bias cross-modal stimulus competition.

Assimilative domain proficiency and performance in chemistry coursework

NASA Astrophysics Data System (ADS)

Byrnes, Scott William

The assimilation and synthesis of knowledge is essential for students to be successful in chemistry, yet not all students synthesize knowledge as intended. The study used the Learning Preference Checklist to classify students into one of three learning modalities -- visual, auditory, or kinesthetic (VAK). It also used the Kolb Learning Style Inventory (KLSI), which utilizes four learning domains - Converging, Accommodating, Diverging, and Assimilating - to explain the students' maturation process by showing shift from any domain towards the Assimilating domain. A shift approaching this domain was considered as improvement in the assimilation and synthesis of knowledge. This pre-experimental one-group pretest-posttest study was used to test the hypothesis that modifying a high school chemistry curriculum to accentuate a student's learning preference would result in a shift towards the Assimilative domain on the KLSI and if there was a correlation between the improvement in student learning and a shift towards the KLSI Assimilating domain. Forty-two high school students were issued the VAK and provided with differentiated instruction via homologous cooperative learning groups. Pre- and post-KLSI and chemistry concepts tests were administered. T test analyses showed no significant shift towards the Assimilating domain. Further Pearson's r analyses showed no significant correlation between the KLSI and exam scores. This study contributes to social change by providing empirical evidence related to the effectiveness infusing learning styles into the science curriculum and the integration of the KLSI to monitor cognitive development as tools in raising standardized test scores and enhancing academic achievement. Results from the study can also inform future research into learning styles through their incorporation into the science curriculum.

The utility and impact of information communication technology (ICT) for pre-registration nurse education: A narrative synthesis systematic review.

PubMed

Webb, Lucy; Clough, Jonathan; O'Reilly, Declan; Wilmott, Danita; Witham, Gary

2017-01-01

To evaluate and summarise the utility and impact of information communication technology (ICT) in enhancing student performance and the learning environment in pre-registration nursing. A systematic review of empirical research across a range of themes in ICT health-related education. Science Direct, Cinahl, AMED, MEDLINE, PubMed, ASSIA, OVID and OVID SP (2008-2014). Further date parameters were imposed by theme. Evidence was reviewed by narrative synthesis, adopting Caldwell's appraisal framework and CASP for qualitative methods. Selection and inclusion was grounded in the PICOS structure, with language requirements (English), and further parameters were guided by theme appropriateness. Fifty studies were selected for review across six domains: reusable learning objects, media, audience response systems, e-portfolios, computer-based assessment and faculty adoption of e-learning. Educational ICT was found to be non-inferior to traditional teaching, while offering benefits to teaching and learning efficiency. Where support is in place, ICT improves the learning environment for staff and students, but human and environmental barriers need to be addressed. This review illuminates more advantages for ICT in nurse training than previously. The key advantage of flexibility is supported, though with little evidence for effect on depth of learning. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Sentiment classification technology based on Markov logic networks

NASA Astrophysics Data System (ADS)

He, Hui; Li, Zhigang; Yao, Chongchong; Zhang, Weizhe

2016-07-01

With diverse online media emerging, there is a growing concern of sentiment classification problem. At present, text sentiment classification mainly utilizes supervised machine learning methods, which feature certain domain dependency. On the basis of Markov logic networks (MLNs), this study proposed a cross-domain multi-task text sentiment classification method rooted in transfer learning. Through many-to-one knowledge transfer, labeled text sentiment classification, knowledge was successfully transferred into other domains, and the precision of the sentiment classification analysis in the text tendency domain was improved. The experimental results revealed the following: (1) the model based on a MLN demonstrated higher precision than the single individual learning plan model. (2) Multi-task transfer learning based on Markov logical networks could acquire more knowledge than self-domain learning. The cross-domain text sentiment classification model could significantly improve the precision and efficiency of text sentiment classification.

Structure of metabotropic glutamate receptor C-terminal domains in contact with interacting proteins.

PubMed

Enz, Ralf

2012-01-01

Metabotropic glutamate receptors (mGluRs) regulate intracellular signal pathways that control several physiological tasks, including neuronal excitability, learning, and memory. This is achieved by the formation of synaptic signal complexes, in which mGluRs assemble with functionally related proteins such as enzymes, scaffolds, and cytoskeletal anchor proteins. Thus, mGluR associated proteins actively participate in the regulation of glutamatergic neurotransmission. Importantly, dysfunction of mGluRs and interacting proteins may lead to impaired signal transduction and finally result in neurological disorders, e.g., night blindness, addiction, epilepsy, schizophrenia, autism spectrum disorders and Parkinson's disease. In contrast to solved crystal structures of extracellular N-terminal domains of some mGluR types, only a few studies analyzed the conformation of intracellular receptor domains. Intracellular C-termini of most mGluR types are subject to alternative splicing and can be further modified by phosphorylation and SUMOylation. In this way, diverse interaction sites for intracellular proteins that bind to and regulate the glutamate receptors are generated. Indeed, most of the known mGluR binding partners interact with the receptors' C-terminal domains. Within the last years, different laboratories analyzed the structure of these domains and described the geometry of the contact surface between mGluR C-termini and interacting proteins. Here, I will review recent progress in the structure characterization of mGluR C-termini and provide an up-to-date summary of the geometry of these domains in contact with binding partners.

Domain-Specific Measurement of Students' Self-Regulated Learning Processes.

ERIC Educational Resources Information Center

Schunk, Dale H.

This article discusses the assessment of self-regulated learning processes as students acquire cognitive skills in specific academic domains. Domain-specific assessment is useful for understanding student learning and for planning instructional activities that help to promote it. Although much psychological research has used general measures of…

Mining e-Learning Domain Concept Map from Academic Articles

ERIC Educational Resources Information Center

Chen, Nian-Shing; Kinshuk; Wei, Chun-Wang; Chen, Hong-Jhe

2008-01-01

Recent researches have demonstrated the importance of concept map and its versatile applications especially in e-Learning. For example, while designing adaptive learning materials, designers need to refer to the concept map of a subject domain. Moreover, concept maps can show the whole picture and core knowledge about a subject domain. Research…

A Framework and a Methodology for Developing Authentic Constructivist e-Learning Environments

ERIC Educational Resources Information Center

Zualkernan, Imran A.

2006-01-01

Semantically rich domains require operative knowledge to solve complex problems in real-world settings. These domains provide an ideal environment for developing authentic constructivist e-learning environments. In this paper we present a framework and a methodology for developing authentic learning environments for such domains. The framework is…

Transformative Learning and Professional Identity Formation During International Health Electives: A Qualitative Study Using Grounded Theory.

PubMed

Sawatsky, Adam P; Nordhues, Hannah C; Merry, Stephen P; Bashir, M Usmaan; Hafferty, Frederic W

2018-03-27

International health electives (IHEs) are widely available during residency and provide unique experiences for trainees. Theoretical models of professional identity formation and transformative learning may provide insight into residents' experiences during IHEs. The purpose of this study was to explore transformative learning and professional identity formation during resident IHEs and characterize the relationship between transformative learning and professional identity formation. The authors used a constructivist grounded theory approach, with the sensitizing concepts of transformative learning and professional identity formation to analyze narrative reflective reports of residents' IHEs. The Mayo International Health Program supports residents from all specialties across three Mayo Clinic sites. In 2015, the authors collected narrative reflective reports from 377 IHE participants dating from 2001-2014. Reflections were coded and themes were organized into a model for transformative learning during IHEs, focusing on professional identity. Five components of transformative learning were identified during IHEs: a disorienting experience; an emotional response; critical reflection; perspective change; and a commitment to future action. Within the component of critical reflection three domains relating to professional identity were identified: making a difference; the doctor-patient relationship; and medicine in its "purest form." Transformation was demonstrated through perspective change and a commitment to future action, including continued service, education, and development. IHEs provide rich experiences for transformative learning and professional identity formation. Understanding the components of transformative learning may provide insight into the interaction between learner, experiences, and the influence of mentors in the process of professional identity formation.

Incomplete Multisource Transfer Learning.

PubMed

Ding, Zhengming; Shao, Ming; Fu, Yun

2018-02-01

Transfer learning is generally exploited to adapt well-established source knowledge for learning tasks in weakly labeled or unlabeled target domain. Nowadays, it is common to see multiple sources available for knowledge transfer, each of which, however, may not include complete classes information of the target domain. Naively merging multiple sources together would lead to inferior results due to the large divergence among multiple sources. In this paper, we attempt to utilize incomplete multiple sources for effective knowledge transfer to facilitate the learning task in target domain. To this end, we propose an incomplete multisource transfer learning through two directional knowledge transfer, i.e., cross-domain transfer from each source to target, and cross-source transfer. In particular, in cross-domain direction, we deploy latent low-rank transfer learning guided by iterative structure learning to transfer knowledge from each single source to target domain. This practice reinforces to compensate for any missing data in each source by the complete target data. While in cross-source direction, unsupervised manifold regularizer and effective multisource alignment are explored to jointly compensate for missing data from one portion of source to another. In this way, both marginal and conditional distribution discrepancy in two directions would be mitigated. Experimental results on standard cross-domain benchmarks and synthetic data sets demonstrate the effectiveness of our proposed model in knowledge transfer from incomplete multiple sources.

A Domain-Specific Account of Self-Regulated Learning: The Cognitive and Metacognitive Activities Involved in Learning through Historical Inquiry

ERIC Educational Resources Information Center

Poitras, Eric G.; Lajoie, Susanne P.

2013-01-01

Educational researchers have recently begun to conceptualize theoretical constructs and mechanisms of metacognitive activities in terms of the features that are specific to particular academic domains and subject matter. In this paper, we propose a framework of domain-specific metacognition in relation to learning through historical inquiry. The…

Developing a Domain Theory Defining and Exemplifying a Learning Theory of Progressive Attainments

ERIC Educational Resources Information Center

Bunderson, C. Victor

2011-01-01

This article defines the concept of Domain Theory, or, when educational measurement is the goal, one might call it a "Learning Theory of Progressive Attainments in X Domain". The concept of Domain Theory is first shown to be rooted in validity theory, then the concept of domain theory is expanded to amplify its necessary but long neglected…

M-Learning: Implications in Learning Domain Specificities, Adaptive Learning, Feedback, Augmented Reality, and the Future of Online Learning

ERIC Educational Resources Information Center

Squires, David R.

2014-01-01

The aim of this paper is to examine the potential and effectiveness of m-learning in the field of Education and Learning domains. The purpose of this research is to illustrate how mobile technology can and is affecting novel change in instruction, from m-learning and the link to adaptive learning, to the uninitiated learner and capacities of…

The Analysis of High School Students' Conceptions of Learning in Different Domains

ERIC Educational Resources Information Center

Sadi, Özlem

2015-01-01

The purpose of this study is to investigate whether or not conceptions of learning diverge in different science domains by identifying high school students' conceptions of learning in physics, chemistry and biology. The Conceptions of Learning Science (COLS) questionnaire was adapted for physics (Conceptions of Learning Physics, COLP), chemistry…

Development of an Assessment Tool to Measure Students' Meaningful Learning in the Undergraduate Chemistry Laboratory

ERIC Educational Resources Information Center

Galloway, Kelli R.; Bretz, Stacey Lowery

2015-01-01

Research on learning in the undergraduate chemistry laboratory necessitates an understanding of students' perspectives of learning. Novak's Theory of Meaningful Learning states that the cognitive (thinking), affective (feeling), and psychomotor (doing) domains must be integrated for meaningful learning to occur. The psychomotor domain is the…

Rapid response learning of brand logo priming: Evidence that brand priming is not dominated by rapid response learning.

PubMed

Boehm, Stephan G; Smith, Ciaran; Muench, Niklas; Noble, Kirsty; Atherton, Catherine

2017-08-31

Repetition priming increases the accuracy and speed of responses to repeatedly processed stimuli. Repetition priming can result from two complementary sources: rapid response learning and facilitation within perceptual and conceptual networks. In conceptual classification tasks, rapid response learning dominates priming of object recognition, but it does not dominate priming of person recognition. This suggests that the relative engagement of network facilitation and rapid response learning depends on the stimulus domain. Here, we addressed the importance of the stimulus domain for rapid response learning by investigating priming in another domain, brands. In three experiments, participants performed conceptual decisions for brand logos. Strong priming was present, but it was not dominated by rapid response learning. These findings add further support to the importance of the stimulus domain for the relative importance of network facilitation and rapid response learning, and they indicate that brand priming is more similar to person recognition priming than object recognition priming, perhaps because priming of both brands and persons requires individuation.

Use of Heuristics to Facilitate Scientific Discovery Learning in a Simulation Learning Environment in a Physics Domain

ERIC Educational Resources Information Center

Veermans, Koen; van Joolingen, Wouter; de Jong, Ton

2006-01-01

This article describes a study into the role of heuristic support in facilitating discovery learning through simulation-based learning. The study compares the use of two such learning environments in the physics domain of collisions. In one learning environment (implicit heuristics) heuristics are only used to provide the learner with guidance…

Multi Agent Reward Analysis for Learning in Noisy Domains

NASA Technical Reports Server (NTRS)

Tumer, Kagan; Agogino, Adrian K.

2005-01-01

In many multi agent learning problems, it is difficult to determine, a priori, the agent reward structure that will lead to good performance. This problem is particularly pronounced in continuous, noisy domains ill-suited to simple table backup schemes commonly used in TD(lambda)/Q-learning. In this paper, we present a new reward evaluation method that allows the tradeoff between coordination among the agents and the difficulty of the learning problem each agent faces to be visualized. This method is independent of the learning algorithm and is only a function of the problem domain and the agents reward structure. We then use this reward efficiency visualization method to determine an effective reward without performing extensive simulations. We test this method in both a static and a dynamic multi-rover learning domain where the agents have continuous state spaces and where their actions are noisy (e.g., the agents movement decisions are not always carried out properly). Our results show that in the more difficult dynamic domain, the reward efficiency visualization method provides a two order of magnitude speedup in selecting a good reward. Most importantly it allows one to quickly create and verify rewards tailored to the observational limitations of the domain.

Visuomotor coordination and cortical connectivity of modular motor learning.

PubMed

Burgos, Pablo I; Mariman, Juan J; Makeig, Scott; Rivera-Lillo, Gonzalo; Maldonado, Pedro E

2018-05-15

The ability to transfer sensorimotor skill components to new actions and the capacity to use skill components from whole actions are characteristic of the adaptability of the human sensorimotor system. However, behavioral evidence suggests complex limitations for transfer after combined or modular learning of motor adaptations. Also, to date, only behavioral analysis of the consequences of the modular learning has been reported, with little understanding of the sensorimotor mechanisms of control and the interaction between cortical areas. We programmed a video game with distorted kinematic and dynamic features to test the ability to combine sensorimotor skill components learned modularly (composition) and the capacity to use separate sensorimotor skill components learned in combination (decomposition). We examined motor performance, eye-hand coordination, and EEG connectivity. When tested for integrated learning, we found that combined practice initially performed better than separated practice, but differences disappeared after integrated practice. Separate learning promotes fewer anticipatory control mechanisms (depending more on feedback control), evidenced in a lower gaze leading behavior and in higher connectivity between visual and premotor domains, in comparison with the combined practice. The sensorimotor system can acquire motor modules in a separated or integrated manner. However, the system appears to require integrated practice to coordinate the adaptations with the skill learning and the networks involved in the integrated behavior. This integration seems to be related to the acquisition of anticipatory mechanism of control and with the decrement of feedback control. © 2018 Wiley Periodicals, Inc.

Learning and serial effects on verbal memory in mild cognitive impairment.

PubMed

Campos-Magdaleno, María; Díaz-Bóveda, Rosalía; Juncos-Rabadán, Onésimo; Facal, David; Pereiro, Arturo X

2016-01-01

The objective of this study was to examine different patterns of learning and episodic memory in 3 mild cognitive impairment (MCI) groups and a control group by administering the California Verbal Learning Test (CVLT) and using serial position effect as a principal variable. The study sample included 3 groups of patients with MCI (n = 90) divided into single-domain amnestic, multiple-domain amnestic, and multiple-domain nonamnestic MCI and a group of healthy controls (n = 60). We compared the performance of each group on several CVLT measures used in previous research, and we included a new measure that provides specific information about the serial effect. Data showed a similar pattern of learning and memory impairment in both amnestic MCI groups (i.e., no differences between the multiple-domain and single-domain subtypes); the recency effect was significantly higher in both amnestic MCI groups than in all other groups, and the primacy effect was only lower in the multiple-domain amnestic MCI subtype. Verbal learning and memory profiles of patients with amnestic MCI were very similar, independent of the presence of deficits in cognitive domains other than episodic memory. Results are discussed in light of the unitary-store model of memory.

Domain-specific and domain-general constraints on word and sequence learning.

PubMed

Archibald, Lisa M D; Joanisse, Marc F

2013-02-01

The relative influences of language-related and memory-related constraints on the learning of novel words and sequences were examined by comparing individual differences in performance of children with and without specific deficits in either language or working memory. Children recalled lists of words in a Hebbian learning protocol in which occasional lists repeated, yielding improved recall over the course of the task on the repeated lists. The task involved presentation of pictures of common nouns followed immediately by equivalent presentations of the spoken names. The same participants also completed a paired-associate learning task involving word-picture and nonword-picture pairs. Hebbian learning was observed for all groups. Domain-general working memory constrained immediate recall, whereas language abilities impacted recall in the auditory modality only. In addition, working memory constrained paired-associate learning generally, whereas language abilities disproportionately impacted novel word learning. Overall, all of the learning tasks were highly correlated with domain-general working memory. The learning of nonwords was additionally related to general intelligence, phonological short-term memory, language abilities, and implicit learning. The results suggest that distinct associations between language- and memory-related mechanisms support learning of familiar and unfamiliar phonological forms and sequences.

Gearsketch: An Adaptive Drawing-Based Learning Environment for the Gears Domain

ERIC Educational Resources Information Center

Leenaars, Frank A.; Joolingen, Wouter R.; Gijlers, Hannie; Bollen, Lars

2014-01-01

GearSketch is a learning environment for the gears domain, aimed at students in the final years of primary school. It is designed for use with a touchscreen device and is based on ideas from drawing-based learning and research on cognitive tutors. At the heart of GearSketch is a domain model that is used to transform learners' strokes into…

Informal Learning of Science. Monograph in the Faculty of Education Research Seminar and Workshop Series.

ERIC Educational Resources Information Center

Dynan, Muredach B., Ed.; Fraser, Barry J., Ed.

Some researchers have argued that students often learn to operate in two domains, the domain of the science context in school, and the domain of everyday life outside of school. Outside of school, students are exposed to many media from which to learn science concepts. This document is one of a series on research seminars at the Western Australian…

Cross-Domain Semi-Supervised Learning Using Feature Formulation.

PubMed

Xingquan Zhu

2011-12-01

Semi-Supervised Learning (SSL) traditionally makes use of unlabeled samples by including them into the training set through an automated labeling process. Such a primitive Semi-Supervised Learning (pSSL) approach suffers from a number of disadvantages including false labeling and incapable of utilizing out-of-domain samples. In this paper, we propose a formative Semi-Supervised Learning (fSSL) framework which explores hidden features between labeled and unlabeled samples to achieve semi-supervised learning. fSSL regards that both labeled and unlabeled samples are generated from some hidden concepts with labeling information partially observable for some samples. The key of the fSSL is to recover the hidden concepts, and take them as new features to link labeled and unlabeled samples for semi-supervised learning. Because unlabeled samples are only used to generate new features, but not to be explicitly included in the training set like pSSL does, fSSL overcomes the inherent disadvantages of the traditional pSSL methods, especially for samples not within the same domain as the labeled instances. Experimental results and comparisons demonstrate that fSSL significantly outperforms pSSL-based methods for both within-domain and cross-domain semi-supervised learning.

A knowledge representation approach using fuzzy cognitive maps for better navigation support in an adaptive learning system.

PubMed

Chrysafiadi, Konstantina; Virvou, Maria

2013-12-01

In this paper a knowledge representation approach of an adaptive and/or personalized tutoring system is presented. The domain knowledge should be represented in a more realistic way in order to allow the adaptive and/or personalized tutoring system to deliver the learning material to each individual learner dynamically taking into account her/his learning needs and her/his different learning pace. To succeed this, the domain knowledge representation has to depict the possible increase or decrease of the learner's knowledge. Considering that the domain concepts that constitute the learning material are not independent from each other, the knowledge representation approach has to allow the system to recognize either the domain concepts that are already partly or completely known for a learner, or the domain concepts that s/he has forgotten, taking into account the learner's knowledge level of the related concepts. In other words, the system should be informed about the knowledge dependencies that exist among the domain concepts of the learning material, as well as the strength on impact of each domain concept on others. Fuzzy Cognitive Maps (FCMs) seem to be an ideal way for representing graphically this kind of information. The suggested knowledge representation approach has been implemented in an e-learning adaptive system for teaching computer programming. The particular system was used by the students of a postgraduate program in the field of Informatics in the University of Piraeus and was compared with a corresponding system, in which the domain knowledge was represented using the most common used technique of network of concepts. The results of the evaluation were very encouraging.

The effect of observational learning on students' performance, processes, and motivation in two creative domains.

PubMed

Groenendijk, Talita; Janssen, Tanja; Rijlaarsdam, Gert; van den Bergh, Huub

2013-03-01

Previous research has shown that observation can be effective for learning in various domains, for example, argumentative writing and mathematics. The question in this paper is whether observational learning can also be beneficial when learning to perform creative tasks in visual and verbal arts. We hypothesized that observation has a positive effect on performance, process, and motivation. We expected similarity in competence between the model and the observer to influence the effectiveness of observation. Sample.  A total of 131 Dutch students (10(th) grade, 15 years old) participated. Two experiments were carried out (one for visual and one for verbal arts). Participants were randomly assigned to one of three conditions; two observational learning conditions and a control condition (learning by practising). The observational learning conditions differed in instructional focus (on the weaker or the more competent model of a pair to be observed). We found positive effects of observation on creative products, creative processes, and motivation in the visual domain. In the verbal domain, observation seemed to affect the creative process, but not the other variables. The model similarity hypothesis was not confirmed. Results suggest that observation may foster learning in creative domains, especially in the visual arts. © 2011 The British Psychological Society.

Comparison of Example-Based Learning and Problem-Based Learning in Engineering Domain

ERIC Educational Resources Information Center

Sern, Lai Chee; Salleh, Kahirol Mohd; Sulaiman, Nor lisa; Mohamad, Mimi Mohaffyza; Yunos, Jailani Md

2015-01-01

The research was conducted to compare the impacts of problem-based learning (PBL) and example-based learning (EBL) on the learning performance in an engineering domain. The research was implemented by means of experimental design. Specifically, a two-group experiment with a pre- and post-test design was used in this research. A total of 37…

Effects of Computer-Based Visual Representation on Mathematics Learning and Cognitive Load

ERIC Educational Resources Information Center

Yung, Hsin I.; Paas, Fred

2015-01-01

Visual representation has been recognized as a powerful learning tool in many learning domains. Based on the assumption that visual representations can support deeper understanding, we examined the effects of visual representations on learning performance and cognitive load in the domain of mathematics. An experimental condition with visual…

Student participation in World Wide Web-based curriculum development of general chemistry

NASA Astrophysics Data System (ADS)

Hunter, William John Forbes

1998-12-01

This thesis describes an action research investigation of improvements to instruction in General Chemistry at Purdue University. Specifically, the study was conducted to guide continuous reform of curriculum materials delivered via the World Wide Web by involving students, instructors, and curriculum designers. The theoretical framework for this study was based upon constructivist learning theory and knowledge claims were developed using an inductive analysis procedure. This results of this study are assertions made in three domains: learning chemistry content via the World Wide Web, learning about learning via the World Wide Web, and learning about participation in an action research project. In the chemistry content domain, students were able to learn chemical concepts that utilized 3-dimensional visualizations, but not textual and graphical information delivered via the Web. In the learning via the Web domain, the use of feedback, the placement of supplementary aids, navigation, and the perception of conceptual novelty were all important to students' use of the Web. In the participation in action research domain, students learned about the complexity of curriculum. development, and valued their empowerment as part of the process.

Use of Commercial Imagery Capabilities in Support of Maritime Domain Awareness

DTIC Science & Technology

2015-06-01

IMAGERY CAPABILITIES IN SUPPORT OF MARITIME DOMAIN AWARENESS by Adam J. Ochs June 2015 Thesis Advisor: Alan D. Scott Second Reader...Paperwork Reduction Project (0704–0188) Washington, DC 20503. 1. AGENCY USE ONLY (Leave blank) 2. REPORT DATE June 2015 3. REPORT TYPE AND DATES...Champaign, 2006 Submitted in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE IN SPACE SYSTEMS OPERATIONS from the

Design and Testing of a Thermostable Platform for Multimerization of Single Domain Antibodies

DTIC Science & Technology

2012-08-01

1 DESIGN AND TESTING OF A THERMOSTABLE PLATFORM FOR MULTIMERIZATION OF SINGLE DOMAIN ANTIBODIES ECBC-TR...Army position unless so designated by other authorizing documents. REPORT DOCUMENTATION PAGE Form Approved OMB No. 0704-0188 Public...ADDRESS. 1. REPORT DATE (DD-MM-YYYY) XX-08-2012 2. REPORT TYPE Final 3. DATES COVERED (From - To) Oct 2008 - Sep 2010 4. TITLE AND SUBTITLE Design

Dating Paleogene Subduction in the Alborán Domain (Alpujárride Complex, S. Spain)

NASA Astrophysics Data System (ADS)

Williams, J. R.; Ashley, K.; Loewy, S. L.; Platt, J. P.

2016-12-01

The multimineral 87Rb/86Sr method has been used in recent studies to date subduction in high-pressure (HP) metamorphic belts of the Mediterranean region. In the Alpujárride Complex, the largest tectonic unit of the Alborán Domain, southern Spain, the timing of burial and HP metamorphism is controversial, with published 40Ar/39Ar white mica ages that range from 48Ma to 25Ma. Dating the HP event is complicated by a pervasive high-temperature (HT) metamorphic overprint (23-19Ma) associated with late-orogenic extension. We have identified 5 rock samples for 87Rb/86Sr dating which preserve a HP equilibrium assemblage: a garnet-staurolite-chloritoid schist, two calcareous Mg-chloritoid schists and two calcareous phyllites with previous 40Ar/39Ar ages of 48Ma and 41Ma. Improved constraints on the time gap between HP and HT metamorphism are important to test geodynamic models of the Alborán Domain, which range from prolonged thickening of continental lithosphere followed by extensional collapse, to punctuated subduction followed by back-arc extension. Furthermore, determining the onset and duration of HP metamorphism has broad implications for whether the Alborán Domain formed in the context of a single Alpine belt, or a separate and local accretionary setting. Lastly, this study will test the advantages and limitations of the 87Rb/86Sr method in a HP domain with a late HT overprint, a very common issue in orogenic systems.

Knowing, Applying, and Reasoning about Arithmetic: Roles of Domain-General and Numerical Skills in Multiple Domains of Arithmetic Learning

ERIC Educational Resources Information Center

Zhang, Xiao; Räsänen, Pekka; Koponen, Tuire; Aunola, Kaisa; Lerkkanen, Marja-Kristiina; Nurmi, Jari-Erik

2017-01-01

The longitudinal relations of domain-general and numerical skills at ages 6-7 years to 3 cognitive domains of arithmetic learning, namely knowing (written computation), applying (arithmetic word problems), and reasoning (arithmetic reasoning) at age 11, were examined for a representative sample of 378 Finnish children. The results showed that…

Implications of Domain-General "Psychological Support Skills" for Transfer of Skill and Acquisition of Expertise

ERIC Educational Resources Information Center

Eccles, David W.; Feltovich, Paul J.

2008-01-01

The article proposes that individuals who acquire certain psychological support skills may experience accelerated learning and enhanced performance in many domains. In support of this proposal, we present evidence that these skills enhance learning and performance, that they are domain-general in that they can be applied in a variety of domains,…

A curriculum for training quality scholars to improve the health and health care of veterans and the community at large.

PubMed

Splaine, Mark E; Aron, David C; Dittus, Robert S; Kiefe, Catarina I; Landefeld, C Seth; Rosenthal, Gary E; Weeks, William B; Batalden, Paul B

2002-01-01

In 1998, the Veterans Health Administration invested in the creation of the Veterans Administration National Quality Scholars Fellowship Program (VAQS) to train physicians in new ways to improve the quality of health care. We describe the curriculum for this program and the lessons learned from our experience to date. The VAQS Fellowship program has developed a core improvement curriculum to train postresidency physicians in the scholarship, research, and teaching of the improvement of health care. The curriculum covers seven domains of knowledge related to improvement: health care as a process; variation and measurement; customer/beneficiary knowledge; leading, following, and making changes in health care; collaboration; social context and accountability; and developing new, locally useful knowledge. We combine specific knowledge about the improvement of health care with the use of adult learning strategies, interactive video, and development of learner competencies. Our program provides insights for medical education to better prepare physicians to participate in and lead the improvement of health care.

Hebb learning, verbal short-term memory, and the acquisition of phonological forms in children.

PubMed

Mosse, Emma K; Jarrold, Christopher

2008-04-01

Recent work using the Hebb effect as a marker for implicit long-term acquisition of serial order has demonstrated a functional equivalence across verbal and visuospatial short-term memory. The current study extends this observation to a sample of five- to six-year-olds using verbal and spatial immediate serial recall and also correlates the magnitude of Hebb learning with explicit measures of word and nonword paired-associate learning. Comparable Hebb effects were observed in both domains, but only nonword learning was significantly related to the magnitude of Hebb learning. Nonword learning was also independently related to individuals' general level of verbal serial recall. This suggests that vocabulary acquisition depends on both a domain-specific short-term memory system and a domain-general process of learning through repetition.

Translating theory into practice: integrating the affective and cognitive learning dimensions for effective instruction in engineering education

NASA Astrophysics Data System (ADS)

Alias, Maizam; Lashari, Tahira Anwar; Abidin Akasah, Zainal; Jahaya Kesot, Mohd.

2014-03-01

Learning in the cognitive domain is highly emphasised and has been widely investigated in engineering education. Lesser emphasis is placed on the affective dimension although the role of affects has been supported by research. The lack of understanding on learning theories and how they may be translated into classroom application of teaching and learning is one factor that contributes to this situation. This paper proposes a working framework for integrating the affective dimension of learning into engineering education that is expected to promote better learning within the cognitive domain. Four major learning theories namely behaviourism, cognitivism, socio-culturalism, and constructivism were analysed and how affects are postulated to influence cognition are identified. The affective domain constructs identified to be important are self-efficacy, attitude and locus of control. Based on the results of the analysis, a framework that integrates methodologies for achieving learning in the cognitive domain with the support of the affective dimension of learning is proposed. It is expected that integrated approach can be used as a guideline to engineering educators in designing effective and sustainable instructional material that would result in the effective engineers for future development.

Multiclass Continuous Correspondence Learning

NASA Technical Reports Server (NTRS)

Bue, Brian D,; Thompson, David R.

2011-01-01

We extend the Structural Correspondence Learning (SCL) domain adaptation algorithm of Blitzer er al. to the realm of continuous signals. Given a set of labeled examples belonging to a 'source' domain, we select a set of unlabeled examples in a related 'target' domain that play similar roles in both domains. Using these 'pivot samples, we map both domains into a common feature space, allowing us to adapt a classifier trained on source examples to classify target examples. We show that when between-class distances are relatively preserved across domains, we can automatically select target pivots to bring the domains into correspondence.

Exploring Effectiveness and Moderators of Language Learning Strategy Instruction on Second Language and Self-Regulated Learning Outcomes

ERIC Educational Resources Information Center

Ardasheva, Yuliya; Wang, Zhe; Adesope, Olusola O.; Valentine, Jeffrey C.

2017-01-01

This meta-analysis synthesized recent research on strategy instruction (SI) effectiveness to estimate SI effects and their moderators for two domains: second/foreign language and self-regulated learning. A total of 37 studies (47 independent samples) for language domain and 16 studies (17 independent samples) for self-regulated learning domain…

The Effect of Observational Learning on Students' Performance, Processes, and Motivation in Two Creative Domains

ERIC Educational Resources Information Center

Groenendijk, Talita; Janssen, Tanja; Rijlaarsdam, Gert; van den Bergh, Huub

2013-01-01

Background. Previous research has shown that observation can be effective for learning in various domains, for example, argumentative writing and mathematics. The question in this paper is whether observational learning can also be beneficial when learning to perform creative tasks in visual and verbal arts. Aims. We hypothesized that observation…

Augmenting the senses: a review on sensor-based learning support.

PubMed

Schneider, Jan; Börner, Dirk; van Rosmalen, Peter; Specht, Marcus

2015-02-11

In recent years sensor components have been extending classical computer-based support systems in a variety of applications domains (sports, health, etc.). In this article we review the use of sensors for the application domain of learning. For that we analyzed 82 sensor-based prototypes exploring their learning support. To study this learning support we classified the prototypes according to the Bloom's taxonomy of learning domains and explored how they can be used to assist on the implementation of formative assessment, paying special attention to their use as feedback tools. The analysis leads to current research foci and gaps in the development of sensor-based learning support systems and concludes with a research agenda based on the findings.

Augmenting the Senses: A Review on Sensor-Based Learning Support

PubMed Central

Schneider, Jan; Börner, Dirk; van Rosmalen, Peter; Specht, Marcus

2015-01-01

In recent years sensor components have been extending classical computer-based support systems in a variety of applications domains (sports, health, etc.). In this article we review the use of sensors for the application domain of learning. For that we analyzed 82 sensor-based prototypes exploring their learning support. To study this learning support we classified the prototypes according to the Bloom's taxonomy of learning domains and explored how they can be used to assist on the implementation of formative assessment, paying special attention to their use as feedback tools. The analysis leads to current research foci and gaps in the development of sensor-based learning support systems and concludes with a research agenda based on the findings. PMID:25679313

Unsupervised Transfer Learning via Multi-Scale Convolutional Sparse Coding for Biomedical Applications

PubMed Central

Chang, Hang; Han, Ju; Zhong, Cheng; Snijders, Antoine M.; Mao, Jian-Hua

2017-01-01

The capabilities of (I) learning transferable knowledge across domains; and (II) fine-tuning the pre-learned base knowledge towards tasks with considerably smaller data scale are extremely important. Many of the existing transfer learning techniques are supervised approaches, among which deep learning has the demonstrated power of learning domain transferrable knowledge with large scale network trained on massive amounts of labeled data. However, in many biomedical tasks, both the data and the corresponding label can be very limited, where the unsupervised transfer learning capability is urgently needed. In this paper, we proposed a novel multi-scale convolutional sparse coding (MSCSC) method, that (I) automatically learns filter banks at different scales in a joint fashion with enforced scale-specificity of learned patterns; and (II) provides an unsupervised solution for learning transferable base knowledge and fine-tuning it towards target tasks. Extensive experimental evaluation of MSCSC demonstrates the effectiveness of the proposed MSCSC in both regular and transfer learning tasks in various biomedical domains. PMID:28129148

Teaching School Science within the Cognitive and Affective Domains

ERIC Educational Resources Information Center

Tan, Kok Siang; Heng, Chong Yong; Tan, Shuhui

2013-01-01

In classrooms, science is usually taught within the cognitive domain while the psychomotor learning domain is achieved through performing science experiments in the laboratory. Although students attend civic and moral education and pastoral care classes where values and life skills are often taught directly, learning experiences in most school…

Domain General Constraints on Statistical Learning

ERIC Educational Resources Information Center

Thiessen, Erik D.

2011-01-01

All theories of language development suggest that learning is constrained. However, theories differ on whether these constraints arise from language-specific processes or have domain-general origins such as the characteristics of human perception and information processing. The current experiments explored constraints on statistical learning of…

Quality of the Home Learning Environment during Preschool Age--Domains and Contextual Conditions

ERIC Educational Resources Information Center

Kluczniok, Katharina; Lehrl, Simone; Kuger, Susanne; Rossbach, Hans-Guenther

2013-01-01

The quality of the home learning environment has been proven to be of major importance for child development, but little is known about the role of domain specificity in promoting early childhood learning at home and its dependence on family background. This article presents a framework of the home learning environment in early childhood that…

A Meta-Analysis of Working Memory Deficits in Children with Learning Difficulties: Is There a Difference between Verbal Domain and Numerical Domain?

ERIC Educational Resources Information Center

Peng, Peng; Fuchs, Douglas

2016-01-01

Children with learning difficulties suffer from working memory (WM) deficits. Yet the specificity of deficits associated with different types of learning difficulties remains unclear. Further research can contribute to our understanding of the nature of WM and the relationship between it and learning difficulties. The current meta-analysis…

Learning Factors Transfer Analysis: Using Learning Curve Analysis to Automatically Generate Domain Models

ERIC Educational Resources Information Center

Pavlik, Philip I. Jr.; Cen, Hao; Koedinger, Kenneth R.

2009-01-01

This paper describes a novel method to create a quantitative model of an educational content domain of related practice item-types using learning curves. By using a pairwise test to search for the relationships between learning curves for these item-types, we show how the test results in a set of pairwise transfer relationships that can be…

Why Johnny can't reengineer health care processes with information technology.

PubMed

Webster, C; McLinden, S; Begler, K

1995-01-01

Many educational institutions are developing curricula that integrate computer and business knowledge and skills concerning a specific industry, such as banking or health care. We have developed a curriculum that emphasizes, equally, medical, computer, and business management concepts. Along the way we confronted a formidable obstacle, namely the domain specificity of the reference disciplines. Knowledge within each domain is sufficiently different from other domains that it reduces the leverage of building on preexisting knowledge and skills. We review this problem from the point of view of cognitive science (in particular, knowledge representation and machine learning) to suggest strategies for coping with incommensurate domain ontologies. These strategies include reflective judgment, implicit learning, abstraction, generalization, analogy, multiple inheritance, project-orientation, selectivity, goal- and failure-driven learning, and case- and story-based learning.

Interrelationship of Knowledge, Interest, and Recall: Assessing a Model of Domain Learning.

ERIC Educational Resources Information Center

Alexander, Patricia A.; And Others

1995-01-01

Two experiments involving 125 college and graduate students examined the interrelationship of subject-matter knowledge, interest, and recall in the field of human immunology and biology and assessed cross-domain performance in physics. Patterns of knowledge, interest, and performance fit well with the premises of the Model of Domain Learning. (SLD)

Example-Based Learning in Heuristic Domains: A Cognitive Load Theory Account

ERIC Educational Resources Information Center

Renkl, Alexander; Hilbert, Tatjana; Schworm, Silke

2009-01-01

One classical instructional effect of cognitive load theory (CLT) is the worked-example effect. Although the vast majority of studies have focused on well-structured and algorithmic sub-domains of mathematics or physics, more recent studies have also analyzed learning with examples from complex domains in which only heuristic solution strategies…

A Mixed-Response Intelligent Tutoring System Based on Learning from Demonstration

ERIC Educational Resources Information Center

Alvarez Xochihua, Omar

2012-01-01

Intelligent Tutoring Systems (ITS) have a significant educational impact on student's learning. However, researchers report time intensive interaction is needed between ITS developers and domain-experts to gather and represent domain knowledge. The challenge is augmented when the target domain is ill-defined. The primary problem resides in…

Domain-general sequence learning deficit in specific language impairment.

PubMed

Lukács, Agnes; Kemény, Ferenc

2014-05-01

Grammar-specific accounts of specific language impairment (SLI) have been challenged by recent claims that language problems are a consequence of impairments in domain-general mechanisms of learning that also play a key role in the process of language acquisition. Our studies were designed to test the generality and nature of this learning deficit by focusing on both sequential and nonsequential, and on verbal and nonverbal, domains. Twenty-nine children with SLI were compared with age-matched typically developing (TD) control children using (a) a serial reaction time task (SRT), testing the learning of motor sequences; (b) an artificial grammar learning (AGL) task, testing the extraction of regularities from auditory sequences; and (c) a weather prediction task (WP), testing probabilistic category learning in a nonsequential task. For the 2 sequence learning tasks, a significantly smaller proportion of children showed evidence of learning in the SLI than in the TD group (χ2 tests, p < .001 for the SRT task, p < .05 for the AGL task), whereas the proportion of learners on the WP task was the same in the 2 groups. The level of learning for SLI learners was comparable with that of TD children on all tasks (with great individual variation). Taken together, these findings suggest that domain-general processes of implicit sequence learning tend to be impaired in SLI. Further research is needed to clarify the relationship of deficits in implicit learning and language.

An Ontology for Learning Services on the Shop Floor

ERIC Educational Resources Information Center

Ullrich, Carsten

2016-01-01

An ontology expresses a common understanding of a domain that serves as a basis of communication between people or systems, and enables knowledge sharing, reuse of domain knowledge, reasoning and thus problem solving. In Technology-Enhanced Learning, especially in Intelligent Tutoring Systems and Adaptive Learning Environments, ontologies serve as…

Do You Hear What I Hear? The Impact of a Hearing Voices Simulation on Affective Domain Attributes in Nursing Students.

PubMed

Ward, Terry D

2015-01-01

Affective domain teaching and learning can facilitate the reduction of stigmatization of clients with mental illness in nursing students. Experiential learning activities such as simulation are regarded as an effective method for facilitating student learning in the affective domain. The project reported here measured the impact of a simulation experience, "Hearing Voices Which Are Distressing," on attitudes, values, and beliefs of accelerated baccalaureate students caring for clients with mental illness who experienced hearing voices.

Strategies to Enhance Online Learning Teams. Team Assessment and Diagnostics Instrument and Agent-based Modeling

DTIC Science & Technology

2010-08-12

Strategies to Enhance Online Learning Teams Team Assessment and Diagnostics Instrument and Agent-based Modeling Tristan E. Johnson, Ph.D. Learning ...REPORT DATE AUG 2010 2. REPORT TYPE 3. DATES COVERED 00-00-2010 to 00-00-2010 4. TITLE AND SUBTITLE Strategies to Enhance Online Learning ...TeamsTeam Strategies to Enhance Online Learning Teams: Team Assessment and Diagnostics Instrument and Agent-based Modeling 5a. CONTRACT NUMBER 5b. GRANT

Shared acoustic codes underlie emotional communication in music and speech—Evidence from deep transfer learning

PubMed Central

Schuller, Björn

2017-01-01

Music and speech exhibit striking similarities in the communication of emotions in the acoustic domain, in such a way that the communication of specific emotions is achieved, at least to a certain extent, by means of shared acoustic patterns. From an Affective Sciences points of view, determining the degree of overlap between both domains is fundamental to understand the shared mechanisms underlying such phenomenon. From a Machine learning perspective, the overlap between acoustic codes for emotional expression in music and speech opens new possibilities to enlarge the amount of data available to develop music and speech emotion recognition systems. In this article, we investigate time-continuous predictions of emotion (Arousal and Valence) in music and speech, and the Transfer Learning between these domains. We establish a comparative framework including intra- (i.e., models trained and tested on the same modality, either music or speech) and cross-domain experiments (i.e., models trained in one modality and tested on the other). In the cross-domain context, we evaluated two strategies—the direct transfer between domains, and the contribution of Transfer Learning techniques (feature-representation-transfer based on Denoising Auto Encoders) for reducing the gap in the feature space distributions. Our results demonstrate an excellent cross-domain generalisation performance with and without feature representation transfer in both directions. In the case of music, cross-domain approaches outperformed intra-domain models for Valence estimation, whereas for Speech intra-domain models achieve the best performance. This is the first demonstration of shared acoustic codes for emotional expression in music and speech in the time-continuous domain. PMID:28658285

Shared acoustic codes underlie emotional communication in music and speech-Evidence from deep transfer learning.

PubMed

Coutinho, Eduardo; Schuller, Björn

2017-01-01

Music and speech exhibit striking similarities in the communication of emotions in the acoustic domain, in such a way that the communication of specific emotions is achieved, at least to a certain extent, by means of shared acoustic patterns. From an Affective Sciences points of view, determining the degree of overlap between both domains is fundamental to understand the shared mechanisms underlying such phenomenon. From a Machine learning perspective, the overlap between acoustic codes for emotional expression in music and speech opens new possibilities to enlarge the amount of data available to develop music and speech emotion recognition systems. In this article, we investigate time-continuous predictions of emotion (Arousal and Valence) in music and speech, and the Transfer Learning between these domains. We establish a comparative framework including intra- (i.e., models trained and tested on the same modality, either music or speech) and cross-domain experiments (i.e., models trained in one modality and tested on the other). In the cross-domain context, we evaluated two strategies-the direct transfer between domains, and the contribution of Transfer Learning techniques (feature-representation-transfer based on Denoising Auto Encoders) for reducing the gap in the feature space distributions. Our results demonstrate an excellent cross-domain generalisation performance with and without feature representation transfer in both directions. In the case of music, cross-domain approaches outperformed intra-domain models for Valence estimation, whereas for Speech intra-domain models achieve the best performance. This is the first demonstration of shared acoustic codes for emotional expression in music and speech in the time-continuous domain.

Mobile Learning Application Based on RSS Feed Technology

ERIC Educational Resources Information Center

Mohanna, Mahmoud; Capus, Laurence

2013-01-01

This paper presents a mobile learning application for a learning course at higher education level. Based on the RSS feed technology, the presented mobile application establishes an in-time communication channel between the instructor and his/her students to keep them up-to-date with all course important dates, instructions and information in…

The Value of Writing-to-Learn when Using Question Prompts to Support Web-Based Learning in Ill-Structured Domains

ERIC Educational Resources Information Center

Papadopoulos, Pantelis M.; Demetriadis, Stavros N.; Stamelos, Ioannis G.; Tsoukalas, Ioannis A.

2011-01-01

This study investigates the effectiveness of two variants of a prompting strategy that guides students to focus on important issues when learning in an ill-structured domain. Students in three groups studied individually Software Project Management (SPM) cases for a week, using a web-based learning environment designed especially for this purpose.…

Cognitive and psychomotor effects of risperidone in schizophrenia and schizoaffective disorder.

PubMed

Houthoofd, Sofie A M K; Morrens, Manuel; Sabbe, Bernard G C

2008-09-01

The aim of this review was to discuss data from double-blind, randomized controlled trials (RCTs) that have investigated the effects of oral and long-acting injectable risperidone on cognitive and psychomotor functioning in patients with schizophrenia or schizoaffective disorder. PubMed/MEDLINE and the Institute of Scientific Information Web of Science database were searched for relevant English-language double-blind RCTs published between March 2000 and July 2008, using the terms schizophrenia, schizoaffective disorder, cognition, risperidone, psychomotor, processing speed, attention, vigilance, working memory, verbal learning, visual learning, reasoning, problem solving, social cognition, MATRICS, and long-acting. Relevant studies included patients with schizophrenia or schizoaffective disorder. Cognitive domains were delineated at the Consensus Conferences of the National Institute of Mental Health-Measurement And Treatment Research to Improve Cognition in Schizophrenia (NIMH-MATRICS). The tests employed to assess each domain and psychomotor functioning, and the within-group and between-group comparisons of risperidone with haloperidol and other atypical antipsychotics, are presented. The results of individual tests were included when they were individually presented and interpretable for either drug; outcomes that were presented as cluster scores or factor structures were excluded. A total of 12 articles were included in this review. Results suggested that the use of oral risperidone appeared to be associated with within-group improvements on the cognitive domains of processing speed, attention/vigilance, verbal and visual learning and memory, and reasoning and problem solving in patients with schizophrenia or schizoaffective disorder. Risperidone and haloperidol seemed to generate similar beneficial effects (on the domains of processing speed, attention/vigilance, [verbal and nonverbal] working memory, and visual learning and memory, as well as psychomotor functioning), although the results for verbal fluency, verbal learning and memory, and reasoning and problem solving were not unanimous, and no comparative data on social cognition were available. Similar cognitive effects were found with risperidone, olanzapine, and quetiapine on the domains of verbal working memory and reasoning and problem solving, as well as verbal fluency. More research is needed on the domains in which study results were contradictory. For olanzapine versus risperidone, these were verbal and visual learning and memory and psychomotor functioning. No comparative data for olanzapine and risperidone were available for the social cognition domain. For quetiapine versus risperidone, the domains in which no unanimity was found were processing speed, attention/vigilance, nonverbal working memory, and verbal learning and memory. The limited available reports on risperidone versus clozapine suggest that: risperidone was associated with improved, and clozapine with worsened, performance on the nonverbal working memory domain; risperidone improved and clozapine did not improve reasoning and problem-solving performance; clozapine improved, and risperidone did not improve, social cognition performance. Use of long-acting injectable risperidone seemed to be associated with improved performance in the domains of attention/vigilance, verbal learning and memory, and reasoning and problem solving, as well as psychomotor functioning. The results for the nonverbal working memory domain were indeterminate, and no clear improvement was seen in the social cognition domain. The domains of processing speed, verbal working memory, and visual learning and memory, as well as verbal fluency, were not assessed. The results of this review of within-group comparisons of oral risperidone suggest that the agent appeared to be associated with improved functioning in the cognitive domains of processing speed, attention/vigilance, verbal and visual learning and memory, and reasoning and problem solving in patients with schizophrenia or schizoaffective disorder. Long-acting injectable risperidone seemed to be associated with improved functioning in the domains of attention/vigilance, verbal learning and memory, and reasoning and problem solving, as well as psychomotor functioning, in patients with schizophrenia or schizoaffective disorder.

Learning and Reasoning in Unknown Domains

NASA Astrophysics Data System (ADS)

Strannegård, Claes; Nizamani, Abdul Rahim; Juel, Jonas; Persson, Ulf

2016-12-01

In the story Alice in Wonderland, Alice fell down a rabbit hole and suddenly found herself in a strange world called Wonderland. Alice gradually developed knowledge about Wonderland by observing, learning, and reasoning. In this paper we present the system Alice In Wonderland that operates analogously. As a theoretical basis of the system, we define several basic concepts of logic in a generalized setting, including the notions of domain, proof, consistency, soundness, completeness, decidability, and compositionality. We also prove some basic theorems about those generalized notions. Then we model Wonderland as an arbitrary symbolic domain and Alice as a cognitive architecture that learns autonomously by observing random streams of facts from Wonderland. Alice is able to reason by means of computations that use bounded cognitive resources. Moreover, Alice develops her belief set by continuously forming, testing, and revising hypotheses. The system can learn a wide class of symbolic domains and challenge average human problem solvers in such domains as propositional logic and elementary arithmetic.

The neuroscience of learning: beyond the Hebbian synapse.

PubMed

Gallistel, C R; Matzel, Louis D

2013-01-01

From the traditional perspective of associative learning theory, the hypothesis linking modifications of synaptic transmission to learning and memory is plausible. It is less so from an information-processing perspective, in which learning is mediated by computations that make implicit commitments to physical and mathematical principles governing the domains where domain-specific cognitive mechanisms operate. We compare the properties of associative learning and memory to the properties of long-term potentiation, concluding that the properties of the latter do not explain the fundamental properties of the former. We briefly review the neuroscience of reinforcement learning, emphasizing the representational implications of the neuroscientific findings. We then review more extensively findings that confirm the existence of complex computations in three information-processing domains: probabilistic inference, the representation of uncertainty, and the representation of space. We argue for a change in the conceptual framework within which neuroscientists approach the study of learning mechanisms in the brain.

Enhancer modularity and the evolution of new traits.

PubMed

Koshikawa, Shigeyuki

2015-01-01

Animals have modular cis-regulatory regions in their genomes, and expression of a single gene is often regulated by multiple enhancers residing in such a region. In the laboratory, and also in natural populations, loss of an enhancer can result in a loss of gene expression. Although only a few examples have been well characterized to date, some studies have suggested that an evolutionary gain of a new enhancer function can establish a new gene expression domain. Our recent study showed that Drosophila guttifera has more enhancers and additional expression domains of the wingless gene during the pupal stage, compared to D. melanogaster, and that these new features appear to have evolved in the ancestral lineage leading to D. guttifera. (1) Gain of a new expression domain of a developmental regulatory gene (toolkit gene), such as wingless, can cause co-option of the expression of its downstream genes to the new domain, resulting in duplication of a preexisting structure at this new body position. Recently, with the advancement of evo-devo studies, we have learned that the developmental regulatory systems are strikingly similar across various animal taxa, in spite of the great diversity of the animals' morphology. Even behind "new" traits, co-options of essential developmental genes from known systems are very common. We previously provided concrete evidence of gains of enhancer activities of a developmental regulatory gene underlying gains of new traits. (1) Broad occurrence of this scenario is testable and should be validated in the future.

Data Analysis and Statistical Methods for the Assessment and Interpretation of Geochronologic Data

NASA Astrophysics Data System (ADS)

Reno, B. L.; Brown, M.; Piccoli, P. M.

2007-12-01

Ages are traditionally reported as a weighted mean with an uncertainty based on least squares analysis of analytical error on individual dates. This method does not take into account geological uncertainties, and cannot accommodate asymmetries in the data. In most instances, this method will understate uncertainty on a given age, which may lead to over interpretation of age data. Geologic uncertainty is difficult to quantify, but is typically greater than analytical uncertainty. These factors make traditional statistical approaches inadequate to fully evaluate geochronologic data. We propose a protocol to assess populations within multi-event datasets and to calculate age and uncertainty from each population of dates interpreted to represent a single geologic event using robust and resistant statistical methods. To assess whether populations thought to represent different events are statistically separate exploratory data analysis is undertaken using a box plot, where the range of the data is represented by a 'box' of length given by the interquartile range, divided at the median of the data, with 'whiskers' that extend to the furthest datapoint that lies within 1.5 times the interquartile range beyond the box. If the boxes representing the populations do not overlap, they are interpreted to represent statistically different sets of dates. Ages are calculated from statistically distinct populations using a robust tool such as the tanh method of Kelsey et al. (2003, CMP, 146, 326-340), which is insensitive to any assumptions about the underlying probability distribution from which the data are drawn. Therefore, this method takes into account the full range of data, and is not drastically affected by outliers. The interquartile range of each population of dates (the interquartile range) gives a first pass at expressing uncertainty, which accommodates asymmetry in the dataset; outliers have a minor affect on the uncertainty. To better quantify the uncertainty, a resistant tool that is insensitive to local misbehavior of data is preferred, such as the normalized median absolute deviations proposed by Powell et al. (2002, Chem Geol, 185, 191-204). We illustrate the method using a dataset of 152 monazite dates determined using EPMA chemical data from a single sample from the Neoproterozoic Brasília Belt, Brazil. Results are compared with ages and uncertainties calculated using traditional methods to demonstrate the differences. The dataset was manually culled into three populations representing discrete compositional domains within chemically-zoned monazite grains. The weighted mean ages and least squares uncertainties for these populations are 633±6 (2σ) Ma for a core domain, 614±5 (2σ) Ma for an intermediate domain and 595±6 (2σ) Ma for a rim domain. Probability distribution plots indicate asymmetric distributions of all populations, which cannot be accounted for with traditional statistical tools. These three domains record distinct ages outside the interquartile range for each population of dates, with the core domain lying in the subrange 642-624 Ma, the intermediate domain 617-609 Ma and the rim domain 606-589 Ma. The tanh estimator yields ages of 631±7 (2σ) for the core domain, 616±7 (2σ) for the intermediate domain and 601±8 (2σ) for the rim domain. Whereas the uncertainties derived using a resistant statistical tool are larger than those derived from traditional statistical tools, the method yields more realistic uncertainties that better address the spread in the dataset and account for asymmetry in the data.

Visual Sequence Learning in Infancy: Domain-General and Domain-Specific Associations with Language

ERIC Educational Resources Information Center

Shafto, Carissa L.; Conway, Christopher M.; Field, Suzanne L.; Houston, Derek M.

2012-01-01

Research suggests that nonlinguistic sequence learning abilities are an important contributor to language development (Conway, Bauernschmidt, Huang, & Pisoni, 2010). The current study investigated visual sequence learning (VSL) as a possible predictor of vocabulary development in infants. Fifty-eight 8.5-month-old infants were presented with a…

Using Mobile Technologies to Create Interwoven Learning Interactions: An Intuitive Design and Its Evaluation

ERIC Educational Resources Information Center

Ting, Yu-Liang

2013-01-01

Numerous studies have proposed and implemented various innovative designs of mobile learning practices, and several pedagogical affordances of mobile technologies in different subject domains have also been suggested. This study proposes a notion for helping instructors design an innovative mobile learning practice in their subject domain. The…

A Study of Two Instructional Sequences Informed by Alternative Learning Progressions in Genetics

ERIC Educational Resources Information Center

Duncan, Ravit Golan; Choi, Jinnie; Castro-Faix, Moraima; Cavera, Veronica L.

2017-01-01

Learning progressions (LPs) are hypothetical models of how learning in a domain develops over time with appropriate instruction. In the domain of genetics, there are two independently developed alternative LPs. The main difference between the two progressions hinges on their assumptions regarding the accessibility of classical (Mendelian) versus…

General and Domain-Specific Self-Concepts of Adults with Learning Disabilities: A Meta-Analysis

ERIC Educational Resources Information Center

Nelson, Jason M.

2012-01-01

The empirical literature investigating general and domain-specific self-concepts of adults with learning disabilities was examined using meta-analytic techniques. Eight inclusion criteria were developed to evaluate this literature and led to the inclusion of 22 studies. Results indicated that adults with learning disabilities reported lower…

Acquiring New Spatial Intuitions: Learning to Reason about Rotations

ERIC Educational Resources Information Center

Pani, John R.; Chariker, Julia H.; Dawson, Thomas E.; Johnson, Nathan

2005-01-01

There are certain simple rotations of objects that most people cannot reason about accurately. Reliable gaps in the understanding of a fundamental physical domain raise the question of how learning to reason in that domain might proceed. Using virtual reality techniques, this project investigated the nature of learning to reason across the domain…

Visible and Thermal Imaging of Sea Ice and Open Water from Coast Guard Arctic Domain Awareness Flights

DTIC Science & Technology

2012-09-30

to better predict the seasonal evolution of the ice cover . APPROACH The Coast Guard Arctic Domain Awareness (ADA) flights based out of Kodiak...does not display a currently valid OMB control number. 1. REPORT DATE 2012 2. REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE...satellite remote sensing data ( MODIS and SSMI) for flight planning before flights and during and after flights for inclusion in the SIZRS-DC database

Windowing of Full Wavefield Data in Multiple Domains to Characterize Angle-Beam Shear Wave Scattering (Postprint)

DTIC Science & Technology

2017-02-01

OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1. REPORT DATE (DD-MM-YY) 2. REPORT TYPE 3 . DATES COVERED (From - To) 19...September 2016 Interim 3 March 2014 – 19 August 2016 4. TITLE AND SUBTITLE WINDOWING OF FULL WAVEFIELD DATA IIN MULTIPLE DOMAINS TO CHARACTERIZE...wavefield baseline subtraction before and after the introduction of a scatterer [2]. Next, a 3 -D Fourier transform is performed to convert the residual

Emotional textile image classification based on cross-domain convolutional sparse autoencoders with feature selection

NASA Astrophysics Data System (ADS)

Li, Zuhe; Fan, Yangyu; Liu, Weihua; Yu, Zeqi; Wang, Fengqin

2017-01-01

We aim to apply sparse autoencoder-based unsupervised feature learning to emotional semantic analysis for textile images. To tackle the problem of limited training data, we present a cross-domain feature learning scheme for emotional textile image classification using convolutional autoencoders. We further propose a correlation-analysis-based feature selection method for the weights learned by sparse autoencoders to reduce the number of features extracted from large size images. First, we randomly collect image patches on an unlabeled image dataset in the source domain and learn local features with a sparse autoencoder. We then conduct feature selection according to the correlation between different weight vectors corresponding to the autoencoder's hidden units. We finally adopt a convolutional neural network including a pooling layer to obtain global feature activations of textile images in the target domain and send these global feature vectors into logistic regression models for emotional image classification. The cross-domain unsupervised feature learning method achieves 65% to 78% average accuracy in the cross-validation experiments corresponding to eight emotional categories and performs better than conventional methods. Feature selection can reduce the computational cost of global feature extraction by about 50% while improving classification performance.

Theory-Led Design of Instruments and Representations in Learning Analytics: Developing a Novel Tool for Orchestration of Online Collaborative Learning

ERIC Educational Resources Information Center

Kelly, Nick; Thompson, Kate; Yeoman, Pippa

2015-01-01

This paper describes theory-led design as a way of developing novel tools for learning analytics (LA). It focuses upon the domain of automated discourse analysis (ADA) of group learning activities to help an instructor to orchestrate online groups in real-time. The paper outlines the literature on the development of LA tools within the domain of…

Automation of energy demand forecasting

NASA Astrophysics Data System (ADS)

Siddique, Sanzad

Automation of energy demand forecasting saves time and effort by searching automatically for an appropriate model in a candidate model space without manual intervention. This thesis introduces a search-based approach that improves the performance of the model searching process for econometrics models. Further improvements in the accuracy of the energy demand forecasting are achieved by integrating nonlinear transformations within the models. This thesis introduces machine learning techniques that are capable of modeling such nonlinearity. Algorithms for learning domain knowledge from time series data using the machine learning methods are also presented. The novel search based approach and the machine learning models are tested with synthetic data as well as with natural gas and electricity demand signals. Experimental results show that the model searching technique is capable of finding an appropriate forecasting model. Further experimental results demonstrate an improved forecasting accuracy achieved by using the novel machine learning techniques introduced in this thesis. This thesis presents an analysis of how the machine learning techniques learn domain knowledge. The learned domain knowledge is used to improve the forecast accuracy.

Moral learning: Psychological and philosophical perspectives.

PubMed

Cushman, Fiery; Kumar, Victor; Railton, Peter

2017-10-01

The past 15years occasioned an extraordinary blossoming of research into the cognitive and affective mechanisms that support moral judgment and behavior. This growth in our understanding of moral mechanisms overshadowed a crucial and complementary question, however: How are they learned? As this special issue of the journal Cognition attests, a new crop of research into moral learning has now firmly taken root. This new literature draws on recent advances in formal methods developed in other domains, such as Bayesian inference, reinforcement learning and other machine learning techniques. Meanwhile, it also demonstrates how learning and deciding in a social domain-and especially in the moral domain-sometimes involves specialized cognitive systems. We review the contributions to this special issue and situate them within the broader contemporary literature. Our review focuses on how we learn moral values and moral rules, how we learn about personal moral character and relationships, and the philosophical implications of these emerging models. Copyright © 2017 Elsevier B.V. All rights reserved.

Identity Exploration in the Dating Domain: The Role of Attachment Dimensions and Parenting Practices

ERIC Educational Resources Information Center

Pittman, Joe F.; Kerpelman, Jennifer L.; Soto, Janet B.; Adler-Baeder, Francesca M.

2012-01-01

We examined relations among perceived parenting practices (support and psychological control), attachment dimensions for romantic relationships (anxiety and avoidance) and exploration of the dating identity among actively dating adolescents in two high school aged samples. In the all female sample of Study 1 (n = 653) and the gender balanced…

Training Peer-Feedback Skills on Geometric Construction Tasks: Role of Domain Knowledge and Peer-Feedback Levels

ERIC Educational Resources Information Center

Alqassab, Maryam; Strijbos, Jan-Willem; Ufer, Stefan

2018-01-01

Peer feedback is widely used to train assessment skills and to support collaborative learning of various learning tasks, but research on peer feedback in the domain of mathematics is limited. Although domain knowledge seems to be a prerequisite for peer-feedback provision, it only recently received attention in the peer-feedback literature. In…

Substructural Regularization With Data-Sensitive Granularity for Sequence Transfer Learning.

PubMed

Sun, Shichang; Liu, Hongbo; Meng, Jiana; Chen, C L Philip; Yang, Yu

2018-06-01

Sequence transfer learning is of interest in both academia and industry with the emergence of numerous new text domains from Twitter and other social media tools. In this paper, we put forward the data-sensitive granularity for transfer learning, and then, a novel substructural regularization transfer learning model (STLM) is proposed to preserve target domain features at substructural granularity in the light of the condition of labeled data set size. Our model is underpinned by hidden Markov model and regularization theory, where the substructural representation can be integrated as a penalty after measuring the dissimilarity of substructures between target domain and STLM with relative entropy. STLM can achieve the competing goals of preserving the target domain substructure and utilizing the observations from both the target and source domains simultaneously. The estimation of STLM is very efficient since an analytical solution can be derived as a necessary and sufficient condition. The relative usability of substructures to act as regularization parameters and the time complexity of STLM are also analyzed and discussed. Comprehensive experiments of part-of-speech tagging with both Brown and Twitter corpora fully justify that our model can make improvements on all the combinations of source and target domains.

Features analysis for identification of date and party hubs in protein interaction network of Saccharomyces Cerevisiae.

PubMed

Mirzarezaee, Mitra; Araabi, Babak N; Sadeghi, Mehdi

2010-12-19

It has been understood that biological networks have modular organizations which are the sources of their observed complexity. Analysis of networks and motifs has shown that two types of hubs, party hubs and date hubs, are responsible for this complexity. Party hubs are local coordinators because of their high co-expressions with their partners, whereas date hubs display low co-expressions and are assumed as global connectors. However there is no mutual agreement on these concepts in related literature with different studies reporting their results on different data sets. We investigated whether there is a relation between the biological features of Saccharomyces Cerevisiae's proteins and their roles as non-hubs, intermediately connected, party hubs, and date hubs. We propose a classifier that separates these four classes. We extracted different biological characteristics including amino acid sequences, domain contents, repeated domains, functional categories, biological processes, cellular compartments, disordered regions, and position specific scoring matrix from various sources. Several classifiers are examined and the best feature-sets based on average correct classification rate and correlation coefficients of the results are selected. We show that fusion of five feature-sets including domains, Position Specific Scoring Matrix-400, cellular compartments level one, and composition pairs with two and one gaps provide the best discrimination with an average correct classification rate of 77%. We study a variety of known biological feature-sets of the proteins and show that there is a relation between domains, Position Specific Scoring Matrix-400, cellular compartments level one, composition pairs with two and one gaps of Saccharomyces Cerevisiae's proteins, and their roles in the protein interaction network as non-hubs, intermediately connected, party hubs and date hubs. This study also confirms the possibility of predicting non-hubs, party hubs and date hubs based on their biological features with acceptable accuracy. If such a hypothesis is correct for other species as well, similar methods can be applied to predict the roles of proteins in those species.

Domain-Specific and Domain-General Learning Factors are Expressed in Genetically Heterogeneous CD-1 mice

PubMed Central

Kolata, Stefan; Light, Kenneth; Matzel, Louis D.

2008-01-01

It has been established that both domain-specific (e.g. spatial) as well as domain-general (general intelligence) factors influence human cognition. However, the separation of these processes has rarely been attempted in studies using laboratory animals. Previously, we have found that the performances of outbred mice across a wide range of learning tasks correlate in such a way that a single factor can explain 30– 44% of the variance between animals. This general learning factor is in some ways qualitatively and quantitatively analogous to general intelligence in humans. The complete structure of cognition in mice, however, has not been explored due to the limited sample sizes of our previous analyses. Here we report a combined analysis from 241 CD-1 mice tested in five primary learning tasks, and a subset of mice tested in two additional learning tasks. At least two (possibly three) of the seven learning tasks placed explicit demands on spatial and/or hippocampus-dependent processing abilities. Consistent with previous findings, we report a robust general factor influencing learning in mice that accounted for 38% of the variance across tasks. In addition, a domain-specific factor was found to account for performance on that subset of tasks that shared a dependence on hippocampal and/or spatial processing. These results provide further evidence for a general learning/cognitive factor in genetically heterogeneous mice. Furthermore (and similar to human cognitive performance), these results suggest a hierarchical structure to cognitive processes in this genetically heterogeneous species. PMID:19129932

Effects of a Peer Competition-based Mobile Learning Approach on Students' Affective Domain Exhibition in Social Studies Courses

ERIC Educational Resources Information Center

Hwang, Gwo-Jen; Chang, Shao-Chen

2016-01-01

One of the important and challenging objectives of social studies courses is to promote students' affective domain exhibition, including learning interest, positive attitudes and local culture identity. In this paper, a location-aware mobile learning approach was proposed based on a competition strategy for conducting local cultural activities in…

A Delphi Study on Technology Enhanced Learning (TEL) Applied on Computer Science (CS) Skills

ERIC Educational Resources Information Center

Porta, Marcela; Mas-Machuca, Marta; Martinez-Costa, Carme; Maillet, Katherine

2012-01-01

Technology Enhanced Learning (TEL) is a new pedagogical domain aiming to study the usage of information and communication technologies to support teaching and learning. The following study investigated how this domain is used to increase technical skills in Computer Science (CS). A Delphi method was applied, using three-rounds of online survey…

Constructing and Modeling Algebraic Statements in the Multiplicative Domain: Investigating Fourth-Grade Student and Teacher Learning

ERIC Educational Resources Information Center

Grandau, Laura

2013-01-01

This study of fourth-grade students and teachers explores mathematics teaching and learning that focuses on discovering and modeling algebraic relationships. The study has two parts: an investigation of how students learn to construct algebraic statements and models for comparisons and measurement situations in the multiplicative domain, and an…

Statistical learning: A powerful mechanism that operates by mere exposure

PubMed Central

Aslin, Richard N.

2015-01-01

How do infants learn so rapidly and with little apparent effort? In 1996, Saffran, Aslin, and Newport reported that 8-month-old human infants could learn the underlying temporal structure of a stream of speech syllables after only two minutes of passive listening. This demonstration of what was called statistical learning, involving no instruction, reinforcement, or feedback, led to dozens of confirmations of this powerful mechanism of implicit learning in a variety of modalities, domains, and species. These findings reveal that infants are not nearly as dependent on explicit forms of instruction as we might have assumed from studies of learning in which children or adults are taught facts such as math or problem solving skills. Instead, at least in some domains, infants soak up the information around them by mere exposure. Learning and development in these domains thus appear to occur automatically and with little active involvement by an instructor (parent or teacher). The details of this statistical learning mechanism are discussed, including how exposure to specific types of information can, under some circumstances, generalize to never-before-observed information, thereby enabling transfer of learning. PMID:27906526

A review on the application of deep learning in system health management

NASA Astrophysics Data System (ADS)

Khan, Samir; Yairi, Takehisa

2018-07-01

Given the advancements in modern technological capabilities, having an integrated health management and diagnostic strategy becomes an important part of a system's operational life-cycle. This is because it can be used to detect anomalies, analyse failures and predict the future state based on up-to-date information. By utilising condition data and on-site feedback, data models can be trained using machine learning and statistical concepts. Once trained, the logic for data processing can be embedded on on-board controllers whilst enabling real-time health assessment and analysis. However, this integration inevitably faces several difficulties and challenges for the community; indicating the need for novel approaches to address this vexing issue. Deep learning has gained increasing attention due to its potential advantages with data classification and feature extraction problems. It is an evolving research area with diverse application domains and hence its use for system health management applications must been researched if it can be used to increase overall system resilience or potential cost benefits for maintenance, repair, and overhaul activities. This article presents a systematic review of artificial intelligence based system health management with an emphasis on recent trends of deep learning within the field. Various architectures and related theories are discussed to clarify its potential. Based on the reviewed work, deep learning demonstrates plausible benefits for fault diagnosis and prognostics. However, there are a number of limitations that hinder its widespread adoption and require further development. Attention is paid to overcoming these challenges, with future opportunities being enumerated.

Impact of corpus domain for sentiment classification: An evaluation study using supervised machine learning techniques

NASA Astrophysics Data System (ADS)

Karsi, Redouane; Zaim, Mounia; El Alami, Jamila

2017-07-01

Thanks to the development of the internet, a large community now has the possibility to communicate and express its opinions and preferences through multiple media such as blogs, forums, social networks and e-commerce sites. Today, it becomes clearer that opinions published on the web are a very valuable source for decision-making, so a rapidly growing field of research called “sentiment analysis” is born to address the problem of automatically determining the polarity (Positive, negative, neutral,…) of textual opinions. People expressing themselves in a particular domain often use specific domain language expressions, thus, building a classifier, which performs well in different domains is a challenging problem. The purpose of this paper is to evaluate the impact of domain for sentiment classification when using machine learning techniques. In our study three popular machine learning techniques: Support Vector Machines (SVM), Naive Bayes and K nearest neighbors(KNN) were applied on datasets collected from different domains. Experimental results show that Support Vector Machines outperforms other classifiers in all domains, since it achieved at least 74.75% accuracy with a standard deviation of 4,08.

Expertise facilitates the transfer of anticipation skill across domains.

PubMed

Rosalie, Simon M; Müller, Sean

2014-02-01

It is unclear whether perceptual-motor skill transfer is based upon similarity between the learning and transfer domains per identical elements theory, or facilitated by an understanding of underlying principles in accordance with general principle theory. Here, the predictions of identical elements theory, general principle theory, and aspects of a recently proposed model for the transfer of perceptual-motor skill with respect to expertise in the learning and transfer domains are examined. The capabilities of expert karate athletes, near-expert karate athletes, and novices to anticipate and respond to stimulus skills derived from taekwondo and Australian football were investigated in ecologically valid contexts using an in situ temporal occlusion paradigm and complex whole-body perceptual-motor skills. Results indicated that the karate experts and near-experts are as capable of using visual information to anticipate and guide motor skill responses as domain experts and near-experts in the taekwondo transfer domain, but only karate experts could perform like domain experts in the Australian football transfer domain. Findings suggest that transfer of anticipation skill is based upon expertise and an understanding of principles but may be supplemented by similarities that exist between the stimulus and response elements of the learning and transfer domains.

Unpacking the Information, Media, and Technology Skills Domain of the New Learning Paradigm

ERIC Educational Resources Information Center

Kivunja, Charles

2015-01-01

Put simply, "Teaching our students so that they become well-equipped with the 21st century skills is the new learning paradigm" (Kivunja, 2014b, p. 85). These skills fall into four domains which the Partnership for 21st Century Skills (P21) identify as the Traditional Core Skills, the Learning and Innovation Skills, the Career and Life…

An Action Research Approach to the Design, Development and Evaluation of an Interactive E-Learning Tutorial in a Cognitive Domain

ERIC Educational Resources Information Center

de Villiers, M. Ruth

2007-01-01

The teaching and learning of a complex section in "Theoretical Computer Science 1" in a distance-education context at the University of South Africa (UNISA) has been enhanced by a supplementary e-learning application called "Relations," which interactively teaches mathematical skills in a cognitive domain. It has tutorial and…

Transfer learning for visual categorization: a survey.

PubMed

Shao, Ling; Zhu, Fan; Li, Xuelong

2015-05-01

Regular machine learning and data mining techniques study the training data for future inferences under a major assumption that the future data are within the same feature space or have the same distribution as the training data. However, due to the limited availability of human labeled training data, training data that stay in the same feature space or have the same distribution as the future data cannot be guaranteed to be sufficient enough to avoid the over-fitting problem. In real-world applications, apart from data in the target domain, related data in a different domain can also be included to expand the availability of our prior knowledge about the target future data. Transfer learning addresses such cross-domain learning problems by extracting useful information from data in a related domain and transferring them for being used in target tasks. In recent years, with transfer learning being applied to visual categorization, some typical problems, e.g., view divergence in action recognition tasks and concept drifting in image classification tasks, can be efficiently solved. In this paper, we survey state-of-the-art transfer learning algorithms in visual categorization applications, such as object recognition, image classification, and human action recognition.

Instructional Curriculum Mapping.

ERIC Educational Resources Information Center

Wager, Walter

Instructional Curriculum Mapping (ICM) is a set of guidelines for diagramming the interrelationships among objectives from different domains of learning. Five major learning domains are identified: (1) intellectual skills; (2) cognitive strategies; (3) verbal information; (4) motor skills; and (5) attitudes. This paper examines the functional…

Critical Domains of Culturally Relevant Leadership Learning: A Call to Transform Leadership Programs.

PubMed

Jones, Tamara Bertrand; Guthrie, Kathy L; Osteen, Laura

2016-12-01

This chapter introduces the critical domains of culturally relevant leadership learning. The model explores how capacity, identity, and efficacy of student leaders interact with dimensions of campus climate. © 2016 Wiley Periodicals, Inc., A Wiley Company.

The TENCompetence Infrastructure: A Learning Network Implementation

NASA Astrophysics Data System (ADS)

Vogten, Hubert; Martens, Harrie; Lemmers, Ruud

The TENCompetence project developed a first release of a Learning Network infrastructure to support individuals, groups and organisations in professional competence development. This infrastructure Learning Network infrastructure was released as open source to the community thereby allowing users and organisations to use and contribute to this development as they see fit. The infrastructure consists of client applications providing the user experience and server components that provide the services to these clients. These services implement the domain model (Koper 2006) by provisioning the entities of the domain model (see also Sect. 18.4) and henceforth will be referenced as domain entity services.

Multi-Instance Metric Transfer Learning for Genome-Wide Protein Function Prediction.

PubMed

Xu, Yonghui; Min, Huaqing; Wu, Qingyao; Song, Hengjie; Ye, Bicui

2017-02-06

Multi-Instance (MI) learning has been proven to be effective for the genome-wide protein function prediction problems where each training example is associated with multiple instances. Many studies in this literature attempted to find an appropriate Multi-Instance Learning (MIL) method for genome-wide protein function prediction under a usual assumption, the underlying distribution from testing data (target domain, i.e., TD) is the same as that from training data (source domain, i.e., SD). However, this assumption may be violated in real practice. To tackle this problem, in this paper, we propose a Multi-Instance Metric Transfer Learning (MIMTL) approach for genome-wide protein function prediction. In MIMTL, we first transfer the source domain distribution to the target domain distribution by utilizing the bag weights. Then, we construct a distance metric learning method with the reweighted bags. At last, we develop an alternative optimization scheme for MIMTL. Comprehensive experimental evidence on seven real-world organisms verifies the effectiveness and efficiency of the proposed MIMTL approach over several state-of-the-art methods.

Missing Modality Transfer Learning via Latent Low-Rank Constraint.

PubMed

Ding, Zhengming; Shao, Ming; Fu, Yun

2015-11-01

Transfer learning is usually exploited to leverage previously well-learned source domain for evaluating the unknown target domain; however, it may fail if no target data are available in the training stage. This problem arises when the data are multi-modal. For example, the target domain is in one modality, while the source domain is in another. To overcome this, we first borrow an auxiliary database with complete modalities, then consider knowledge transfer across databases and across modalities within databases simultaneously in a unified framework. The contributions are threefold: 1) a latent factor is introduced to uncover the underlying structure of the missing modality from the known data; 2) transfer learning in two directions allows the data alignment between both modalities and databases, giving rise to a very promising recovery; and 3) an efficient solution with theoretical guarantees to the proposed latent low-rank transfer learning algorithm. Comprehensive experiments on multi-modal knowledge transfer with missing target modality verify that our method can successfully inherit knowledge from both auxiliary database and source modality, and therefore significantly improve the recognition performance even when test modality is inaccessible in the training stage.

iLearning, The Game Changer

DTIC Science & Technology

2012-03-21

physical kinesthetically. Auditory learners ’ best receive and process information by hearing what is presented. Visual learners ’ best learn by reading or...Leader Development Strategy , which highlights essential elements necessary for future leader development. Inquiry Based Learning (IBL) is a learner ...ADDRESS. 1. REPORT DATE (DD-MM-YYYY) 03-21-2012 2. REPORT TYPE Strategy Research Project 3. DATES COVERED (From - To) 4. TITLE AND SUBTITLE

Negative Allosteric Modulators Selective for The NR2B Subtype of The NMDA Receptor Impair Cognition in Multiple Domains

PubMed Central

Weed, Michael R; Bookbinder, Mark; Polino, Joseph; Keavy, Deborah; Cardinal, Rudolf N; Simmermacher-Mayer, Jean; Cometa, Fu-ni L; King, Dalton; Thangathirupathy, Srinivasan; Macor, John E; Bristow, Linda J

2016-01-01

Antidepressant activity of N-methyl-D-aspartate (NMDA) receptor antagonists and negative allosteric modulators (NAMs) has led to increased investigation of their behavioral pharmacology. NMDA antagonists, such as ketamine, impair cognition in multiple species and in multiple cognitive domains. However, studies with NR2B subtype-selective NAMs have reported mixed results in rodents including increased impulsivity, no effect on cognition, impairment or even improvement of some cognitive tasks. To date, the effects of NR2B-selective NAMs on cognitive tests have not been reported in nonhuman primates. The current study evaluated two selective NR2B NAMs, CP101,606 and BMT-108908, along with the nonselective NMDA antagonists, ketamine and AZD6765, in the nonhuman primate Cambridge Neuropsychological Test Automated Battery (CANTAB) list-based delayed match to sample (list-DMS) task. Ketamine and the two NMDA NR2B NAMs produced selective impairments in memory in the list-DMS task. AZD6765 impaired performance in a non-specific manner. In a separate cohort, CP101,606 impaired performance of the nonhuman primate CANTAB visuo-spatial Paired Associates Learning (vsPAL) task with a selective impairment at more difficult conditions. The results of these studies clearly show that systemic administration of a selective NR2B NAM can cause transient cognitive impairment in multiple cognitive domains. PMID:26105137

Adaptive Semantic and Social Web-based learning and assessment environment for the STEM

NASA Astrophysics Data System (ADS)

Babaie, Hassan; Atchison, Chris; Sunderraman, Rajshekhar

2014-05-01

We are building a cloud- and Semantic Web-based personalized, adaptive learning environment for the STEM fields that integrates and leverages Social Web technologies to allow instructors and authors of learning material to collaborate in semi-automatic development and update of their common domain and task ontologies and building their learning resources. The semi-automatic ontology learning and development minimize issues related to the design and maintenance of domain ontologies by knowledge engineers who do not have any knowledge of the domain. The social web component of the personal adaptive system will allow individual and group learners to interact with each other and discuss their own learning experience and understanding of course material, and resolve issues related to their class assignments. The adaptive system will be capable of representing key knowledge concepts in different ways and difficulty levels based on learners' differences, and lead to different understanding of the same STEM content by different learners. It will adapt specific pedagogical strategies to individual learners based on their characteristics, cognition, and preferences, allow authors to assemble remotely accessed learning material into courses, and provide facilities for instructors to assess (in real time) the perception of students of course material, monitor their progress in the learning process, and generate timely feedback based on their understanding or misconceptions. The system applies a set of ontologies that structure the learning process, with multiple user friendly Web interfaces. These include the learning ontology (models learning objects, educational resources, and learning goal); context ontology (supports adaptive strategy by detecting student situation), domain ontology (structures concepts and context), learner ontology (models student profile, preferences, and behavior), task ontologies, technological ontology (defines devices and places that surround the student), pedagogy ontology, and learner ontology (defines time constraint, comment, profile).

Teachers' Spatial Anxiety Relates to 1st-and 2nd-Graders' Spatial Learning

ERIC Educational Resources Information Center

Gunderson, Elizabeth A.; Ramirez, Gerardo; Beilock, Sian L.; Levine, Susan C.

2013-01-01

Teachers' anxiety about an academic domain, such as math, can impact students' learning in that domain. We asked whether this relation held in the domain of spatial skill, given the importance of spatial skill for success in math and science and its malleability at a young age. We measured 1st-and 2nd-grade teachers' spatial anxiety…

Natural-Annotation-based Unsupervised Construction of Korean-Chinese Domain Dictionary

NASA Astrophysics Data System (ADS)

Liu, Wuying; Wang, Lin

2018-03-01

The large-scale bilingual parallel resource is significant to statistical learning and deep learning in natural language processing. This paper addresses the automatic construction issue of the Korean-Chinese domain dictionary, and presents a novel unsupervised construction method based on the natural annotation in the raw corpus. We firstly extract all Korean-Chinese word pairs from Korean texts according to natural annotations, secondly transform the traditional Chinese characters into the simplified ones, and finally distill out a bilingual domain dictionary after retrieving the simplified Chinese words in an extra Chinese domain dictionary. The experimental results show that our method can automatically build multiple Korean-Chinese domain dictionaries efficiently.

Lessons Learned from the Node 1 Temperature and Humidity Control Subsystem Design

NASA Technical Reports Server (NTRS)

Williams, David E.

2010-01-01

Node 1 flew to the International Space Station (ISS) on Flight 2A during December 1998. To date the National Aeronautics and Space Administration (NASA) has learned a lot of lessons from this module based on its history of approximately two years of acceptance testing on the ground and currently its twelve years on-orbit. This paper will provide an overview of the ISS Environmental Control and Life Support (ECLS) design of the Node 1 Temperature and Humidity Control (THC) subsystem and it will document some of the lessons that have been learned to date for this subsystem and it will document some of the lessons that have been learned to date for these subsystems based on problems prelaunch, problems encountered on-orbit, and operational problems/concerns. It is hoped that documenting these lessons learned from ISS will help in preventing them in future Programs. 1

Sleep and motor learning: Is there room for consolidation?

PubMed

Pan, Steven C; Rickard, Timothy C

2015-07-01

It is widely believed that sleep is critical to the consolidation of learning and memory. In some skill domains, performance has been shown to improve by 20% or more following sleep, suggesting that sleep enhances learning. However, recent work suggests that those performance gains may be driven by several factors that are unrelated to sleep consolidation, inviting a reconsideration of sleep's theoretical role in the consolidation of procedural memories. Here we report the first comprehensive investigation of that possibility for the case of motor sequence learning. Quantitative meta-analyses involving 34 articles, 88 experimental groups and 1,296 subjects confirmed the empirical pattern of a large performance gain following sleep and a significantly smaller gain following wakefulness. However, the results also confirm strong moderating effects of 4 previously hypothesized variables: averaging in the calculation of prepost gain scores, build-up of reactive inhibition over training, time of testing, and training duration, along with 1 supplemental variable, elderly status. With those variables accounted for, there was no evidence that sleep enhances learning. Thus, the literature speaks against, rather than for, the enhancement hypothesis. Overall there was relatively better performance after sleep than after wakefulness, suggesting that sleep may stabilize memory. That effect, however, was not consistent across different experimental designs. We conclude that sleep does not enhance motor learning and that the role of sleep in the stabilization of memory cannot be conclusively determined based on the literature to date. We discuss challenges and opportunities for the field, make recommendations for improved experimental design, and suggest approaches to data analysis that eliminate confounds due to averaging over online learning. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

The Experimental Research on E-Learning Instructional Design Model Based on Cognitive Flexibility Theory

NASA Astrophysics Data System (ADS)

Cao, Xianzhong; Wang, Feng; Zheng, Zhongmei

The paper reports an educational experiment on the e-Learning instructional design model based on Cognitive Flexibility Theory, the experiment were made to explore the feasibility and effectiveness of the model in promoting the learning quality in ill-structured domain. The study performed the experiment on two groups of students: one group learned through the system designed by the model and the other learned by the traditional method. The results of the experiment indicate that the e-Learning designed through the model is helpful to promote the intrinsic motivation, learning quality in ill-structured domains, ability to resolve ill-structured problem and creative thinking ability of the students.

75 FR 56115 - Center for Scientific Review; Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-15

... Processes Integrated Review Group, Biobehavioral Regulation, Learning and Ethology Study Section. Date..., Biobehavioral Regulation, Learning and Ethology. Date: October 8, 2010. Time: 9 a.m. to 10 a.m. Agenda: To..., Cellular and Developmental Neuroscience Integrated Review Group, Biophysics of Neural Systems Study Section...

75 FR 26261 - Center for Scientific Review; Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-11

... Committee: Emerging Technologies and Training Neurosciences Integrated Review Group; Molecular Neurogenetics...; Biobehavioral Regulation, Learning and Ethology. Date: June 4, 2010. Time: 9 a.m. to 10 a.m. Agenda: To review... Panel; ARRA: Biobehavioral Regulation, Learning and Ethology Competitive Revisions. Date: June 4, 2010...

Training self-assessment and task-selection skills to foster self-regulated learning: Do trained skills transfer across domains?

PubMed

Raaijmakers, Steven F; Baars, Martine; Paas, Fred; van Merriënboer, Jeroen J G; van Gog, Tamara

2018-01-01

Students' ability to accurately self-assess their performance and select a suitable subsequent learning task in response is imperative for effective self-regulated learning. Video modeling examples have proven effective for training self-assessment and task-selection skills, and-importantly-such training fostered self-regulated learning outcomes. It is unclear, however, whether trained skills would transfer across domains. We investigated whether skills acquired from training with either a specific, algorithmic task-selection rule or a more general heuristic task-selection rule in biology would transfer to self-regulated learning in math. A manipulation check performed after the training confirmed that both algorithmic and heuristic training improved task-selection skills on the biology problems compared with the control condition. However, we found no evidence that students subsequently applied the acquired skills during self-regulated learning in math. Future research should investigate how to support transfer of task-selection skills across domains.

Training self‐assessment and task‐selection skills to foster self‐regulated learning: Do trained skills transfer across domains?

PubMed Central

Baars, Martine; Paas, Fred; van Merriënboer, Jeroen J. G.; van Gog, Tamara

2018-01-01

Summary Students' ability to accurately self‐assess their performance and select a suitable subsequent learning task in response is imperative for effective self‐regulated learning. Video modeling examples have proven effective for training self‐assessment and task‐selection skills, and—importantly—such training fostered self‐regulated learning outcomes. It is unclear, however, whether trained skills would transfer across domains. We investigated whether skills acquired from training with either a specific, algorithmic task‐selection rule or a more general heuristic task‐selection rule in biology would transfer to self‐regulated learning in math. A manipulation check performed after the training confirmed that both algorithmic and heuristic training improved task‐selection skills on the biology problems compared with the control condition. However, we found no evidence that students subsequently applied the acquired skills during self‐regulated learning in math. Future research should investigate how to support transfer of task‐selection skills across domains. PMID:29610547

An Efficient Semi-supervised Learning Approach to Predict SH2 Domain Mediated Interactions.

PubMed

Kundu, Kousik; Backofen, Rolf

2017-01-01

Src homology 2 (SH2) domain is an important subclass of modular protein domains that plays an indispensable role in several biological processes in eukaryotes. SH2 domains specifically bind to the phosphotyrosine residue of their binding peptides to facilitate various molecular functions. For determining the subtle binding specificities of SH2 domains, it is very important to understand the intriguing mechanisms by which these domains recognize their target peptides in a complex cellular environment. There are several attempts have been made to predict SH2-peptide interactions using high-throughput data. However, these high-throughput data are often affected by a low signal to noise ratio. Furthermore, the prediction methods have several additional shortcomings, such as linearity problem, high computational complexity, etc. Thus, computational identification of SH2-peptide interactions using high-throughput data remains challenging. Here, we propose a machine learning approach based on an efficient semi-supervised learning technique for the prediction of 51 SH2 domain mediated interactions in the human proteome. In our study, we have successfully employed several strategies to tackle the major problems in computational identification of SH2-peptide interactions.

Machine learning-based coreference resolution of concepts in clinical documents

PubMed Central

Ware, Henry; Mullett, Charles J; El-Rawas, Oussama

2012-01-01

Objective Coreference resolution of concepts, although a very active area in the natural language processing community, has not yet been widely applied to clinical documents. Accordingly, the 2011 i2b2 competition focusing on this area is a timely and useful challenge. The objective of this research was to collate coreferent chains of concepts from a corpus of clinical documents. These concepts are in the categories of person, problems, treatments, and tests. Design A machine learning approach based on graphical models was employed to cluster coreferent concepts. Features selected were divided into domain independent and domain specific sets. Training was done with the i2b2 provided training set of 489 documents with 6949 chains. Testing was done on 322 documents. Results The learning engine, using the un-weighted average of three different measurement schemes, resulted in an F measure of 0.8423 where no domain specific features were included and 0.8483 where the feature set included both domain independent and domain specific features. Conclusion Our machine learning approach is a promising solution for recognizing coreferent concepts, which in turn is useful for practical applications such as the assembly of problem and medication lists from clinical documents. PMID:22582205

The Effect of Self-Explaining on Robust Learning

ERIC Educational Resources Information Center

Hausmann, Robert G. M.; VanLehn, Kurt

2010-01-01

Self-explaining is a domain-independent learning strategy that generally leads to a robust understanding of the domain material. However, there are two potential explanations for its effectiveness. First, self-explanation generates additional "content" that does not exist in the instructional materials. Second, when compared to…

Impaired Value Learning for Faces in Preschoolers With Autism Spectrum Disorder.

PubMed

Wang, Quan; DiNicola, Lauren; Heymann, Perrine; Hampson, Michelle; Chawarska, Katarzyna

2018-01-01

One of the common findings in autism spectrum disorder (ASD) is limited selective attention toward social objects, such as faces. Evidence from both human and nonhuman primate studies suggests that selection of objects for processing is guided by the appraisal of object values. We hypothesized that impairments in selective attention in ASD may reflect a disruption of a system supporting learning about object values in the social domain. We examined value learning in social (faces) and nonsocial (fractals) domains in preschoolers with ASD (n = 25) and typically developing (TD) controls (n = 28), using a novel value learning task implemented on a gaze-contingent eye-tracking platform consisting of value learning and a selective attention choice test. Children with ASD performed more poorly than TD controls on the social value learning task, but both groups performed similarly on the nonsocial task. Within-group comparisons indicated that value learning in TD children was enhanced on the social compared to the nonsocial task, but no such enhancement was seen in children with ASD. Performance in the social and nonsocial conditions was correlated in the ASD but not in the TD group. The study provides support for a domain-specific impairment in value learning for faces in ASD, and suggests that, in ASD, value learning in social and nonsocial domains may rely on a shared mechanism. These findings have implications both for models of selective social attention deficits in autism and for identification of novel treatment targets. Copyright © 2017 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Learning from Experience, Volume 2: Lessons from the U.S. Navy’s Ohio, Seawolf, and Virginia Submarine Programs

DTIC Science & Technology

2011-01-01

valid OMB control number. 1. REPORT DATE 2011 2. REPORT TYPE 3. DATES COVERED 00-00-2011 to 00-00-2011 4. TITLE AND SUBTITLE Learning from...MURPHY MARK V. ARENA • KRISTY N. KAMARCK • GORDON T. LEE LEARNING FROM EXPERIENCE Lessons from the U.S. Navy’s Ohio, Seawolf, and Virginia Submarine...managers of new programs may not have the benefit of learning from the challenges faced and the issues solved in past programs. Recognizing the

APOE epsilon4 is associated with impaired verbal learning in patients with MS.

PubMed

Koutsis, G; Panas, M; Giogkaraki, E; Potagas, C; Karadima, G; Sfagos, C; Vassilopoulos, D

2007-02-20

To investigate the effect of APOE epsilon4 on different cognitive domains in a population of Greek patients with multiple sclerosis (MS). A total of 125 patients with MS and 43 controls were included in this study and underwent neuropsychological assessment with Rao's Brief Repeatable Battery. All patients with MS were genotyped for APOE. The effect of APOE epsilon4 on different cognitive domains was investigated. Fifty-one percent of patients with MS were cognitively impaired. E4 carriers had a sixfold increase in the relative risk of impairment in verbal learning vs noncarriers (OR 6.28, 95% CI 1.74 to 22.69). This effect was domain-specific and was not observed in other cognitive domains assessed by the battery. We found an association of APOE epsilon4 with impaired verbal learning in patients with multiple sclerosis.

Qualitative analysis of student beliefs and attitudes after an objective structured clinical evaluation: implications for affective domain learning in undergraduate nursing education.

PubMed

Cazzell, Mary; Rodriguez, Amber

2011-12-01

This qualitative study explored the feelings, beliefs, and attitudes of senior-level undergraduate pediatric nursing students upon completion of a medication administration Objective Structured Clinical Evaluation (OSCE). The affective domain is the most neglected domain in higher education, although it is deemed the "gateway to learning." Quantitative assessments of clinical skills performed during OSCEs usually address two of the three domains of learning: cognitive (knowledge) and psychomotor skills. Twenty students volunteered to participate in focus groups (10 per group) and were asked three questions relevant to their feelings, beliefs, and attitudes about their OSCE experiences. Students integrated the attitude of safety first into future practice but felt that anxiety, loss of control, reaction under pressure, and no feedback affected their ability to connect the OSCE performance with future clinical practice. The findings affect future affective domain considerations in the development, modification, and assessment of OSCEs across the undergraduate nursing curriculum.

Apoptosis Induction by Targeting Interferon Gamma Receptor 2 (IFNgammaR2) in Prostate Cancer: Ligand (IFNgamma) Independent Novel Function of IFNgammaR2 as a Bax Inhibitor

DTIC Science & Technology

2016-10-01

DATE October 2016 2. REPORT TYPE Final report 3 . DATES COVERED 1 Aug 2012 - 31 Jul 2016 4. TITLE AND SUBTITLE Apoptosis Induction by Targeting...identify the subtype of prostate cancer that can be effectively treated by IFNγR2-targeting technologies (Months 13-36) Task 3 : Determination of the...N-terminal 53 amino acids is known to be auto-inhibitory domain that keeps Bax in the cytosol[ 3 ]. If this domain is cleaved, Bax is known to be

Polarity Control and Growth of Lateral Polarity Structures in AlN

DTIC Science & Technology

2013-05-10

domains. Transmission electron microscopy shows mixed edge-screw type dislocations with polarity-dependent dislocation bending. Raman 1. REPORT DATE (DD-MM...polarity-dependent dislocation bending. Raman spectroscopy reveals compressively strained Al-polar and relaxed N-polar domains. The near band edge...dislocation bending. Raman spectroscopy reveals compressively strained Al-polar and relaxed N-polar domains. The near band edge luminescence consists of

Elaborative-Interrogation and Prior-Knowledge Effects on Learning of Facts.

ERIC Educational Resources Information Center

Woloshyn, Vera E.; And Others

1992-01-01

The differences among elaborative-interrogation, reading-to-understand, and no-exposure control conditions with familiar domain material in contrast to unfamiliar domain material were studied for 50 Canadian and 50 west German undergraduates. Results provide evidence of effects of both elaborative interrogation and prior knowledge on learning.…

Validating Domain Ontologies: A Methodology Exemplified for Concept Maps

ERIC Educational Resources Information Center

Steiner, Christina M.; Albert, Dietrich

2017-01-01

Ontologies play an important role as knowledge domain representations in technology-enhanced learning and instruction. Represented in form of concept maps they are commonly used as teaching and learning material and have the potential to enhance positive educational outcomes. To ensure the effective use of an ontology representing a knowledge…

Exploring Children's Passion for Learning in Six Domains

ERIC Educational Resources Information Center

Coleman, Laurence J.; Guo, Aige

2013-01-01

Passion for learning (PFL) in children is a phenomenon that is little understood. The experience of PFL was studied with phenomenological and qualitative modes of inquiry. Case studies of six domains (acting, reading, filmmaking, spelling, math, and preaching) describe how the passion developed using the voices of children and parents. Their…

Curriculum Development in the Affective Domain.

ERIC Educational Resources Information Center

Feldman, Beverly Neuer

This document presents an affective domain curriculum and reviews the behaviorist and humanist learning theories on which it is based. Recognizing the significance of the relationship between positive self concept and ability to learn, the affective curriculum was designed for the continuing development of self concept and interpersonal skills in…

Expert Concept Mapping Study on Mobile Learning

ERIC Educational Resources Information Center

Borner, Dirk; Glahn, Christian; Stoyanov, Slavi; Kalz, Marco; Specht, Marcus

2010-01-01

Purpose: The present paper introduces concept mapping as a structured participative conceptualization approach to identify clusters of ideas and opinions generated by experts within the domain of mobile learning. Utilizing this approach, the paper aims to contribute to a definition of key domain characteristics by identifying the main educational…

Phonetic Diversity, Statistical Learning, and Acquisition of Phonology

ERIC Educational Resources Information Center

Pierrehumbert, Janet B.

2003-01-01

In learning to perceive and produce speech, children master complex language-specific patterns. Daunting language-specific variation is found both in the segmental domain and in the domain of prosody and intonation. This article reviews the challenges posed by results in phonetic typology and sociolinguistics for the theory of language…

Cross-domain and multi-task transfer learning of deep convolutional neural network for breast cancer diagnosis in digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir; Helvie, Mark A.; Richter, Caleb; Cha, Kenny

2018-02-01

We propose a cross-domain, multi-task transfer learning framework to transfer knowledge learned from non-medical images by a deep convolutional neural network (DCNN) to medical image recognition task while improving the generalization by multi-task learning of auxiliary tasks. A first stage cross-domain transfer learning was initiated from ImageNet trained DCNN to mammography trained DCNN. 19,632 regions-of-interest (ROI) from 2,454 mass lesions were collected from two imaging modalities: digitized-screen film mammography (SFM) and full-field digital mammography (DM), and split into training and test sets. In the multi-task transfer learning, the DCNN learned the mass classification task simultaneously from the training set of SFM and DM. The best transfer network for mammography was selected from three transfer networks with different number of convolutional layers frozen. The performance of single-task and multitask transfer learning on an independent SFM test set in terms of the area under the receiver operating characteristic curve (AUC) was 0.78+/-0.02 and 0.82+/-0.02, respectively. In the second stage cross-domain transfer learning, a set of 12,680 ROIs from 317 mass lesions on DBT were split into validation and independent test sets. We first studied the data requirements for the first stage mammography trained DCNN by varying the mammography training data from 1% to 100% and evaluated its learning on the DBT validation set in inference mode. We found that the entire available mammography set provided the best generalization. The DBT validation set was then used to train only the last four fully connected layers, resulting in an AUC of 0.90+/-0.04 on the independent DBT test set.

Accelerating Imitation Learning in Relational Domains via Transfer by Initialization

DTIC Science & Technology

2013-08-28

Warcraft , regulation of traffic lights, logistics, and a variety of planning domains. A supervised learning method for imitation learning was recently...some information about the world (traffic density at a signal, distance to the goal etc.). We assume a functional parametrization over the policy and...strategy (RTS) game engine written in C based off the Warcraft series of games. Like all RTS games, it allows multiple agents to be controlled

Prediction in Health Domain Using Bayesian Networks Optimization Based on Induction Learning Techniques

NASA Astrophysics Data System (ADS)

Felgaer, Pablo; Britos, Paola; García-Martínez, Ramón

A Bayesian network is a directed acyclic graph in which each node represents a variable and each arc a probabilistic dependency; they are used to provide: a compact form to represent the knowledge and flexible methods of reasoning. Obtaining it from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper we define an automatic learning method that optimizes the Bayesian networks applied to classification, using a hybrid method of learning that combines the advantages of the induction techniques of the decision trees (TDIDT-C4.5) with those of the Bayesian networks. The resulting method is applied to prediction in health domain.

26 CFR 1.1445-4 - Liability of agents.

Code of Federal Regulations, 2013 CFR

2013-04-01

... soon as possible after learning of the false certification or statement, but not later than the date of the transfer (prior to the transferee's payment of consideration). If an agent first learns of a false certification or statement after the date of the transfer, notice must be given by the third day following that...

26 CFR 1.1445-4 - Liability of agents.

Code of Federal Regulations, 2014 CFR

2014-04-01

... soon as possible after learning of the false certification or statement, but not later than the date of the transfer (prior to the transferee's payment of consideration). If an agent first learns of a false certification or statement after the date of the transfer, notice must be given by the third day following that...

26 CFR 1.1445-4 - Liability of agents.

Code of Federal Regulations, 2012 CFR

2012-04-01

... soon as possible after learning of the false certification or statement, but not later than the date of the transfer (prior to the transferee's payment of consideration). If an agent first learns of a false certification or statement after the date of the transfer, notice must be given by the third day following that...

Equal Partners. Austin Teenagers Learn To Expect Respect in Dating Relationships.

ERIC Educational Resources Information Center

Harrison, Mary M.

1997-01-01

Describes the Teen Dating Violence Project, a 24-week program in the Austin (Texas) schools that offers single sex support groups for young men and women involved in violent relationships. Learning to build equitable and respectful relationships often involves unlearning gender stereotypes, but the program shows that attitudes can change. (SLD)

Profiles of Identity Exploration and Commitment across Domains

ERIC Educational Resources Information Center

Bartoszuk, Karin; Pittman, Joe F.

2010-01-01

We examined the relationships between family structure, gender and age and profiles of identity exploration and commitment in the ideological (occupation, values, politics, religion, gender roles) and interpersonal identity (dating, friendships, and family) domains among 388 young adults. The general profile revealed low exploration in both…

Cognition before curriculum: rethinking the integration of basic science and clinical learning.

PubMed

Kulasegaram, Kulamakan Mahan; Martimianakis, Maria Athina; Mylopoulos, Maria; Whitehead, Cynthia R; Woods, Nicole N

2013-10-01

Integrating basic science and clinical concepts in the undergraduate medical curriculum is an important challenge for medical education. The health professions education literature includes a variety of educational strategies for integrating basic science and clinical concepts at multiple levels of the curriculum. To date, assessment of this literature has been limited. In this critical narrative review, the authors analyzed literature published in the last 30 years (1982-2012) using a previously published integration framework. They included studies that documented approaches to integration at the level of programs, courses, or teaching sessions and that aimed to improve learning outcomes. The authors evaluated these studies for evidence of successful integration and to identify factors that contribute to integration. Several strategies at the program and course level are well described but poorly evaluated. Multiple factors contribute to successful learning, so identifying how interventions at these levels result in successful integration is difficult. Evidence from session-level interventions and experimental studies suggests that integration can be achieved if learning interventions attempt to link basic and clinical science in a causal relationship. These interventions attend to how learners connect different domains of knowledge and suggest that successful integration requires learners to build cognitive associations between basic and clinical science. One way of understanding the integration of basic and clinical science is as a cognitive activity occurring within learners. This perspective suggests that learner-centered, content-focused, and session-level-oriented strategies can achieve cognitive integration.

Untrained Chimpanzees (Pan troglodytes schweinfurthii) Fail to Imitate Novel Actions

PubMed Central

Tennie, Claudio; Call, Josep; Tomasello, Michael

2012-01-01

Background Social learning research in apes has focused on social learning in the technical (problem solving) domain - an approach that confounds action and physical information. Successful subjects in such studies may have been able to perform target actions not as a result of imitation learning but because they had learnt some technical aspect, for example, copying the movements of an apparatus (i.e., different forms of emulation learning). Methods Here we present data on action copying by non-enculturated and untrained chimpanzees when physical information is removed from demonstrations. To date, only one such study (on gesture copying in a begging context) has been conducted – with negative results. Here we have improved this methodology and have also added non-begging test situations (a possible confound of the earlier study). Both familiar and novel actions were used as targets. Prior to testing, a trained conspecific demonstrator was rewarded for performing target actions in view of observers. All but one of the tested chimpanzees already failed to copy familiar actions. When retested with a novel target action, also the previously successful subject failed to copy – and he did so across several contexts. Conclusion Chimpanzees do not seem to copy novel actions, and only some ever copy familiar ones. Due to our having tested only non-enculturated and untrained chimpanzees, the performance of our test subjects speak more than most other studies of the general (dis-)ability of chimpanzees to copy actions, and especially novel actions. PMID:22905102

Statistical learning: a powerful mechanism that operates by mere exposure.

PubMed

Aslin, Richard N

2017-01-01

How do infants learn so rapidly and with little apparent effort? In 1996, Saffran, Aslin, and Newport reported that 8-month-old human infants could learn the underlying temporal structure of a stream of speech syllables after only 2 min of passive listening. This demonstration of what was called statistical learning, involving no instruction, reinforcement, or feedback, led to dozens of confirmations of this powerful mechanism of implicit learning in a variety of modalities, domains, and species. These findings reveal that infants are not nearly as dependent on explicit forms of instruction as we might have assumed from studies of learning in which children or adults are taught facts such as math or problem solving skills. Instead, at least in some domains, infants soak up the information around them by mere exposure. Learning and development in these domains thus appear to occur automatically and with little active involvement by an instructor (parent or teacher). The details of this statistical learning mechanism are discussed, including how exposure to specific types of information can, under some circumstances, generalize to never-before-observed information, thereby enabling transfer of learning. WIREs Cogn Sci 2017, 8:e1373. doi: 10.1002/wcs.1373 For further resources related to this article, please visit the WIREs website. © 2016 Wiley Periodicals, Inc.

Evaluation of a chronic disease management system for the treatment and management of diabetes in primary health care practices in Ontario: an observational study.

PubMed

O'Reilly, D J; Bowen, J M; Sebaldt, R J; Petrie, A; Hopkins, R B; Assasi, N; MacDougald, C; Nunes, E; Goeree, R

2014-01-01

Computerized chronic disease management systems (CDMSs), when aligned with clinical practice guidelines, have the potential to effectively impact diabetes care. The objective was to measure the difference between optimal diabetes care and actual diabetes care before and after the introduction of a computerized CDMS. This 1-year, prospective, observational, pre/post study evaluated the use of a CDMS with a diabetes patient registry and tracker in family practices using patient enrolment models. Aggregate practice-level data from all rostered diabetes patients were analyzed. The primary outcome measure was the change in proportion of patients with up-to-date "ABC" monitoring frequency (i.e., hemoglobin A1c, blood pressure, and cholesterol). Changes in the frequency of other practice care and treatment elements (e.g., retinopathy screening) were also determined. Usability and satisfaction with the CDMS were measured. Nine sites, 38 health care providers, and 2,320 diabetes patients were included. The proportion of patients with up-to-date ABC (12%), hemoglobin A1c (45%), and cholesterol (38%) monitoring did not change over the duration of the study. The proportion of patients with up-to-date blood pressure monitoring improved, from 16% to 20%. Data on foot examinations, retinopathy screening, use of angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers, and documentation of self-management goals were not available or not up to date at baseline for 98% of patients. By the end of the study, attitudes of health care providers were more negative on the Training, Usefulness, Daily Practice, and Support from the Service Provider domains of the CDMS, but more positive on the Learning, Using, Practice Planning, CDMS, and Satisfaction domains. Few practitioners used the CDMS, so it was difficult to draw conclusions about its efficacy. Simply giving health care providers a potentially useful technology will not ensure its use. This real-world evaluation of a web-based CDMS for diabetes failed to impact physician practice due to limited use of the system. Patients and health care providers need timely access to information to ensure proper diabetes care. This study looked at whether a computer-based system at the doctor's office could improve diabetes management. However, few clinics and health care providers used the system, so no improvement in diabetes care was seen.

A Robust Geometric Model for Argument Classification

NASA Astrophysics Data System (ADS)

Giannone, Cristina; Croce, Danilo; Basili, Roberto; de Cao, Diego

Argument classification is the task of assigning semantic roles to syntactic structures in natural language sentences. Supervised learning techniques for frame semantics have been recently shown to benefit from rich sets of syntactic features. However argument classification is also highly dependent on the semantics of the involved lexicals. Empirical studies have shown that domain dependence of lexical information causes large performance drops in outside domain tests. In this paper a distributional approach is proposed to improve the robustness of the learning model against out-of-domain lexical phenomena.

Transductive multi-view zero-shot learning.

PubMed

Fu, Yanwei; Hospedales, Timothy M; Xiang, Tao; Gong, Shaogang

2015-11-01

Most existing zero-shot learning approaches exploit transfer learning via an intermediate semantic representation shared between an annotated auxiliary dataset and a target dataset with different classes and no annotation. A projection from a low-level feature space to the semantic representation space is learned from the auxiliary dataset and applied without adaptation to the target dataset. In this paper we identify two inherent limitations with these approaches. First, due to having disjoint and potentially unrelated classes, the projection functions learned from the auxiliary dataset/domain are biased when applied directly to the target dataset/domain. We call this problem the projection domain shift problem and propose a novel framework, transductive multi-view embedding, to solve it. The second limitation is the prototype sparsity problem which refers to the fact that for each target class, only a single prototype is available for zero-shot learning given a semantic representation. To overcome this problem, a novel heterogeneous multi-view hypergraph label propagation method is formulated for zero-shot learning in the transductive embedding space. It effectively exploits the complementary information offered by different semantic representations and takes advantage of the manifold structures of multiple representation spaces in a coherent manner. We demonstrate through extensive experiments that the proposed approach (1) rectifies the projection shift between the auxiliary and target domains, (2) exploits the complementarity of multiple semantic representations, (3) significantly outperforms existing methods for both zero-shot and N-shot recognition on three image and video benchmark datasets, and (4) enables novel cross-view annotation tasks.

The Cost of Concreteness: The Effect of Nonessential Information on Analogical Transfer

ERIC Educational Resources Information Center

Kaminski, Jennifer A.; Sloutsky, Vladimir M.; Heckler, Andrew F.

2013-01-01

Most theories of analogical transfer focus on similarities between the learning and transfer domains, where transfer is more likely between domains that share common surface features, similar elements, or common interpretations of structure. We suggest that characteristics of the learning instantiation alone can give rise to different levels of…

Belief-Desire Reasoning as a Process of Selection

ERIC Educational Resources Information Center

Leslie, Alan M.; German, Tim P.; Polizzi, Pamela

2005-01-01

Human learning may depend upon domain specialized mechanisms. A plausible example is rapid, early learning about the thoughts and feelings of other people. A major achievement in this domain, at about age four in the typically developing child, is the ability to solve problems in which the child attributes false beliefs to other people and…

Applying Cognitive Science to Education: Thinking and Learning in Scientific and Other Complex Domains

ERIC Educational Resources Information Center

Reif, Frederick

2008-01-01

Many students find it difficult to learn the kinds of knowledge and thinking required by college or high school courses in mathematics, science, or other complex domains. Thus they often emerge with significant misconceptions, fragmented knowledge, and inadequate problem-solving skills. Most instructors or textbook authors approach their teaching…

The Contributions of Domain-General and Numerical Factors to Third-Grade Arithmetic Skills and Mathematical Learning Disability

ERIC Educational Resources Information Center

Cowan, Richard; Powell, Daisy

2014-01-01

Explanations of the marked individual differences in elementary school mathematical achievement and mathematical learning disability (MLD or dyscalculia) have involved domain-general factors (working memory, reasoning, processing speed, and oral language) and numerical factors that include single-digit processing efficiency and multidigit skills…

Making Connections in Math: Activating a Prior Knowledge Analogue Matters for Learning

ERIC Educational Resources Information Center

Sidney, Pooja G.; Alibali, Martha W.

2015-01-01

This study investigated analogical transfer of conceptual structure from a prior-knowledge domain to support learning in a new domain of mathematics: division by fractions. Before a procedural lesson on division by fractions, fifth and sixth graders practiced with a surface analogue (other operations on fractions) or a structural analogue (whole…

Demonstrable Competence: An Assessment Method for Competency Domains in Learning and Leadership Doctoral Program

ERIC Educational Resources Information Center

Rausch, David W.; Crawford, Elizabeth K.

2013-01-01

Through this paper, we describe how a doctoral program in Learning and Leadership combines the best of both worlds from theory based programs and applied programs. Participants work from their embedded professional practice underpinned with the theoretical constructs of the program's seven foundational competency domains. Competencies are…

Can Being Scared Cause Tummy Aches? Naive Theories, Ambiguous Evidence, and Preschoolers' Causal Inferences

ERIC Educational Resources Information Center

Schulz, Laura E.; Bonawitz, Elizabeth Baraff; Griffiths, Thomas L.

2007-01-01

Causal learning requires integrating constraints provided by domain-specific theories with domain-general statistical learning. In order to investigate the interaction between these factors, the authors presented preschoolers with stories pitting their existing theories against statistical evidence. Each child heard 2 stories in which 2 candidate…

The Influence of Curriculum on Master's Students' Perceived Abilities in Four Domains of Graduateness

ERIC Educational Resources Information Center

Steur, Jessica; Jansen, Ellen; Hofman, Adriaan

2016-01-01

Potentially all university graduates, regardless of the discipline they have studied, are expected to have obtained generic learning outcomes, which we refer to as "graduateness." This study investigates the extent to which learning programmes' emphasis on graduateness affects students' perceived abilities in the domains of graduateness.…

Technical Report: Kindergarten Early Learning Scale

ERIC Educational Resources Information Center

Riley-Ayers, Shannon; Jung, Kwanghee; Quinn, Jorie

2014-01-01

The Kindergarten Early Learning Scale (KELS) was developed as a concise observational assessment for young children. It examines three domains including (1) Math/Science, (2) Social Emotional/Social Studies, and (3) Language and Literacy, with a total of 10 items across the domains. Scores reported for each of the 10 items are based upon…

Neuropsychological profile in adult schizophrenia measured with the CMINDS.

PubMed

van Erp, Theo G M; Preda, Adrian; Turner, Jessica A; Callahan, Shawn; Calhoun, Vince D; Bustillo, Juan R; Lim, Kelvin O; Mueller, Bryon; Brown, Gregory G; Vaidya, Jatin G; McEwen, Sarah; Belger, Aysenil; Voyvodic, James; Mathalon, Daniel H; Nguyen, Dana; Ford, Judith M; Potkin, Steven G

2015-12-30

Schizophrenia neurocognitive domain profiles are predominantly based on paper-and-pencil batteries. This study presents the first schizophrenia domain profile based on the Computerized Multiphasic Interactive Neurocognitive System (CMINDS(®)). Neurocognitive domain z-scores were computed from computerized neuropsychological tests, similar to those in the Measurement and Treatment Research to Improve Cognition in Schizophrenia Consensus Cognitive Battery (MCCB), administered to 175 patients with schizophrenia and 169 demographically similar healthy volunteers. The schizophrenia domain profile order by effect size was Speed of Processing (d=-1.14), Attention/Vigilance (d=-1.04), Working Memory (d=-1.03), Verbal Learning (d=-1.02), Visual Learning (d=-0.91), and Reasoning/Problem Solving (d=-0.67). There were no significant group by sex interactions, but overall women, compared to men, showed advantages on Attention/Vigilance, Verbal Learning, and Visual Learning compared to Reasoning/Problem Solving on which men showed an advantage over women. The CMINDS can readily be employed in the assessment of cognitive deficits in neuropsychiatric disorders; particularly in large-scale studies that may benefit most from electronic data capture. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Profiling medical school learning environments in Malaysia: a validation study of the Johns Hopkins Learning Environment Scale.

PubMed

Tackett, Sean; Bakar, Hamidah Abu; Shilkofski, Nicole A; Coady, Niamh; Rampal, Krishna; Wright, Scott

2015-01-01

While a strong learning environment is critical to medical student education, the assessment of medical school learning environments has confounded researchers. Our goal was to assess the validity and utility of the Johns Hopkins Learning Environment Scale (JHLES) for preclinical students at three Malaysian medical schools with distinct educational and institutional models. Two schools were new international partnerships, and the third was school leaver program established without international partnership. First- and second-year students responded anonymously to surveys at the end of the academic year. The surveys included the JHLES, a 28-item survey using five-point Likert scale response options, the Dundee Ready Educational Environment Measure (DREEM), the most widely used method to assess learning environments internationally, a personal growth scale, and single-item global learning environment assessment variables. The overall response rate was 369/429 (86%). After adjusting for the medical school year, gender, and ethnicity of the respondents, the JHLES detected differences across institutions in four out of seven domains (57%), with each school having a unique domain profile. The DREEM detected differences in one out of five categories (20%). The JHLES was more strongly correlated than the DREEM to two thirds of the single-item variables and the personal growth scale. The JHLES showed high internal reliability for the total score (α=0.92) and the seven domains (α, 0.56-0.85). The JHLES detected variation between learning environment domains across three educational settings, thereby creating unique learning environment profiles. Interpretation of these profiles may allow schools to understand how they are currently supporting trainees and identify areas needing attention.

Human-level control through deep reinforcement learning.

PubMed

Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A; Veness, Joel; Bellemare, Marc G; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg, Shane; Hassabis, Demis

2015-02-26

The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successfully in situations approaching real-world complexity, however, agents are confronted with a difficult task: they must derive efficient representations of the environment from high-dimensional sensory inputs, and use these to generalize past experience to new situations. Remarkably, humans and other animals seem to solve this problem through a harmonious combination of reinforcement learning and hierarchical sensory processing systems, the former evidenced by a wealth of neural data revealing notable parallels between the phasic signals emitted by dopaminergic neurons and temporal difference reinforcement learning algorithms. While reinforcement learning agents have achieved some successes in a variety of domains, their applicability has previously been limited to domains in which useful features can be handcrafted, or to domains with fully observed, low-dimensional state spaces. Here we use recent advances in training deep neural networks to develop a novel artificial agent, termed a deep Q-network, that can learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning. We tested this agent on the challenging domain of classic Atari 2600 games. We demonstrate that the deep Q-network agent, receiving only the pixels and the game score as inputs, was able to surpass the performance of all previous algorithms and achieve a level comparable to that of a professional human games tester across a set of 49 games, using the same algorithm, network architecture and hyperparameters. This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.

Profiling medical school learning environments in Malaysia: a validation study of the Johns Hopkins Learning Environment Scale

PubMed Central

Tackett, Sean; Bakar, Hamidah Abu; Shilkofski, Nicole A.; Coady, Niamh; Rampal, Krishna; Wright, Scott

2015-01-01

Purpose: While a strong learning environment is critical to medical student education, the assessment of medical school learning environments has confounded researchers. Our goal was to assess the validity and utility of the Johns Hopkins Learning Environment Scale (JHLES) for preclinical students at three Malaysian medical schools with distinct educational and institutional models. Two schools were new international partnerships, and the third was school leaver program established without international partnership. Methods: First- and second-year students responded anonymously to surveys at the end of the academic year. The surveys included the JHLES, a 28-item survey using five-point Likert scale response options, the Dundee Ready Educational Environment Measure (DREEM), the most widely used method to assess learning environments internationally, a personal growth scale, and single-item global learning environment assessment variables. Results: The overall response rate was 369/429 (86%). After adjusting for the medical school year, gender, and ethnicity of the respondents, the JHLES detected differences across institutions in four out of seven domains (57%), with each school having a unique domain profile. The DREEM detected differences in one out of five categories (20%). The JHLES was more strongly correlated than the DREEM to two thirds of the single-item variables and the personal growth scale. The JHLES showed high internal reliability for the total score (α=0.92) and the seven domains (α, 0.56-0.85). Conclusion: The JHLES detected variation between learning environment domains across three educational settings, thereby creating unique learning environment profiles. Interpretation of these profiles may allow schools to understand how they are currently supporting trainees and identify areas needing attention. PMID:26165949

Human-level control through deep reinforcement learning

NASA Astrophysics Data System (ADS)

Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A.; Veness, Joel; Bellemare, Marc G.; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K.; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg, Shane; Hassabis, Demis

2015-02-01

The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successfully in situations approaching real-world complexity, however, agents are confronted with a difficult task: they must derive efficient representations of the environment from high-dimensional sensory inputs, and use these to generalize past experience to new situations. Remarkably, humans and other animals seem to solve this problem through a harmonious combination of reinforcement learning and hierarchical sensory processing systems, the former evidenced by a wealth of neural data revealing notable parallels between the phasic signals emitted by dopaminergic neurons and temporal difference reinforcement learning algorithms. While reinforcement learning agents have achieved some successes in a variety of domains, their applicability has previously been limited to domains in which useful features can be handcrafted, or to domains with fully observed, low-dimensional state spaces. Here we use recent advances in training deep neural networks to develop a novel artificial agent, termed a deep Q-network, that can learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning. We tested this agent on the challenging domain of classic Atari 2600 games. We demonstrate that the deep Q-network agent, receiving only the pixels and the game score as inputs, was able to surpass the performance of all previous algorithms and achieve a level comparable to that of a professional human games tester across a set of 49 games, using the same algorithm, network architecture and hyperparameters. This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.

Measuring meaningful learning in the undergraduate chemistry laboratory

NASA Astrophysics Data System (ADS)

Galloway, Kelli R.

The undergraduate chemistry laboratory has been an essential component in chemistry education for over a century. The literature includes reports on investigations of singular aspects laboratory learning and attempts to measure the efficacy of reformed laboratory curriculum as well as faculty goals for laboratory learning which found common goals among instructors for students to learn laboratory skills, techniques, experimental design, and to develop critical thinking skills. These findings are important for improving teaching and learning in the undergraduate chemistry laboratory, but research is needed to connect the faculty goals to student perceptions. This study was designed to explore students' ideas about learning in the undergraduate chemistry laboratory. Novak's Theory of Meaningful Learning was used as a guide for the data collection and analysis choices for this research. Novak's theory states that in order for meaningful learning to occur the cognitive, affective, and psychomotor domains must be integrated. The psychomotor domain is inherent in the chemistry laboratory, but the extent to which the cognitive and affective domains are integrated is unknown. For meaningful learning to occur in the laboratory, students must actively integrate both the cognitive domain and the affective domains into the "doing" of their laboratory work. The Meaningful Learning in the Laboratory Instrument (MLLI) was designed to measure students' cognitive and affective expectations and experiences within the context of conducting experiments in the undergraduate chemistry laboratory. Evidence for the validity and reliability of the data generated by the MLLI were collected from multiple quantitative studies: a one semester study at one university, a one semester study at 15 colleges and universities across the United States, and a longitudinal study where the MLLI was administered 6 times during two years of general and organic chemistry laboratory courses. Results from these studies revealed students' narrow cognitive expectations for learning that go largely unmet by their experiences and diverse affective expectations and experiences. Concurrently, a qualitative study was carried out to describe and characterize students' cognitive and affective experiences in the undergraduate chemistry laboratory. Students were video recorded while performing one of their regular laboratory experiments and then interviewed about their experiences. The students' descriptions of their learning experiences were characterized by their overreliance on following the experimental procedure correctly rather than developing process-oriented problem solving skills. Future research could use the MLLI to intentionally compare different types of laboratory curricula or environments.

Improvement of learning domains of nursing students with the use of authentic assessment pedagogy in clinical practice.

PubMed

Chong, Edmund Jun Meng; Lim, Jessica Shih Wei; Liu, Yuchan; Lau, Yvonne Yen Lin; Wu, Vivien Xi

2016-09-01

With evolving healthcare demands, nursing educators need to constantly review their teaching methodologies in order to enhance learners' knowledge and competency of skills in the clinical settings. Learning is an active process in which meaning is accomplished on the basis of experience and that authentic assessment pedagogy will enable nursing students to play an active part in their learning. The study was conducted with an aim to examine nursing students' learning domains through the introduction of the authentic assessment pedagogy during their clinical practice. A quasi-experimental study (n = 54) was conducted over a period of 10 weeks at a local tertiary hospital. The experimental group was exposed to the authentic assessment pedagogy and were taught to use the assessment rubrics as an instrument to help enhance their learning. Students were assessed and scored according to the assessment rubrics, which were categorized into four domains; cognitive, psychomotor, affective and critical thinking abilities. The findings indicated that an overall score for the four domains between the experimental and control groups were significant, with p value of <0.05. Critical thinking scores were indicative of consistent improvement within the experimental group. The findings confirmed that learning outcomes of the nursing students were enhanced through the early introduction of the authentic assessment pedagogy in the clinical setting. Copyright © 2016 Elsevier Ltd. All rights reserved.

Grounding cognitive control in associative learning.

PubMed

Abrahamse, Elger; Braem, Senne; Notebaert, Wim; Verguts, Tom

2016-07-01

Cognitive control covers a broad range of cognitive functions, but its research and theories typically remain tied to a single domain. Here we outline and review an associative learning perspective on cognitive control in which control emerges from associative networks containing perceptual, motor, and goal representations. Our review identifies 3 trending research themes that are shared between the domains of conflict adaptation, task switching, response inhibition, and attentional control: Cognitive control is context-specific, can operate in the absence of awareness, and is modulated by reward. As these research themes can be envisaged as key characteristics of learning, we propose that their joint emergence across domains is not coincidental but rather reflects a (latent) growth of interest in learning-based control. Associative learning has the potential for providing broad-scaled integration to cognitive control theory, and offers a promising avenue for understanding cognitive control as a self-regulating system without postulating an ill-defined set of homunculi. We discuss novel predictions, theoretical implications, and immediate challenges that accompany an associative learning perspective on cognitive control. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Cognitive biases, linguistic universals, and constraint-based grammar learning.

PubMed

Culbertson, Jennifer; Smolensky, Paul; Wilson, Colin

2013-07-01

According to classical arguments, language learning is both facilitated and constrained by cognitive biases. These biases are reflected in linguistic typology-the distribution of linguistic patterns across the world's languages-and can be probed with artificial grammar experiments on child and adult learners. Beginning with a widely successful approach to typology (Optimality Theory), and adapting techniques from computational approaches to statistical learning, we develop a Bayesian model of cognitive biases and show that it accounts for the detailed pattern of results of artificial grammar experiments on noun-phrase word order (Culbertson, Smolensky, & Legendre, 2012). Our proposal has several novel properties that distinguish it from prior work in the domains of linguistic theory, computational cognitive science, and machine learning. This study illustrates how ideas from these domains can be synthesized into a model of language learning in which biases range in strength from hard (absolute) to soft (statistical), and in which language-specific and domain-general biases combine to account for data from the macro-level scale of typological distribution to the micro-level scale of learning by individuals. Copyright © 2013 Cognitive Science Society, Inc.

Susan Loucks-Horsley learning model in light pollution theme: based on a new taxonomy for science education

NASA Astrophysics Data System (ADS)

Liliawati, W.; Utama, J. A.; Fauziah, H.

2016-08-01

The curriculum in Indonesia recommended that science teachers in the elementary and intermediate schools should have interdisciplinary ability in science. However, integrated learning still has not been implemented optimally. This research is designing and applying integrated learning with Susan Loucks-Horsley model in light pollution theme. It can be showed how the student's achievements based on new taxonomy of science education with five domains: knowing & understanding, science process skill, creativity, attitudinal and connecting & applying. This research use mixed methods with concurrent embedded design. The subject is grade 8 of junior high school students in Bandung as many as 27 students. The Instrument have been employed has 28 questions test mastery of concepts, observations sheet and moral dilemma test. The result shows that integrated learning with model Susan Loucks-Horsley is able to increase student's achievement and positive characters on light pollution theme. As the results are the average normalized gain of knowing and understanding domain reach in lower category, the average percentage of science process skill domain reach in good category, the average percentage of creativity and connecting domain reach respectively in good category and attitudinal domain the average percentage is over 75% in moral knowing and moral feeling.

The desktop interface in intelligent tutoring systems

NASA Technical Reports Server (NTRS)

Baudendistel, Stephen; Hua, Grace

1987-01-01

The interface between an Intelligent Tutoring System (ITS) and the person being tutored is critical to the success of the learning process. If the interface to the ITS is confusing or non-supportive of the tutored domain, the effectiveness of the instruction will be diminished or lost entirely. Consequently, the interface to an ITS should be highly integrated with the domain to provide a robust and semantically rich learning environment. In building an ITS for ZetaLISP on a LISP Machine, a Desktop Interface was designed to support a programming learning environment. Using the bitmapped display, windows, and mouse, three desktops were designed to support self-study and tutoring of ZetaLISP. Through organization, well-defined boundaries, and domain support facilities, the desktops provide substantial flexibility and power for the student and facilitate learning ZetaLISP programming while screening the student from the complex LISP Machine environment. The student can concentrate on learning ZetaLISP programming and not on how to operate the interface or a LISP Machine.

Profile of mathematics anxiety of 7th graders

NASA Astrophysics Data System (ADS)

Udil, Patrisius Afrisno; Kusmayadi, Tri Atmojo; Riyadi

2017-08-01

Mathematics anxiety is one of the important factors affect students mathematics achievement. This present research investigates profile of students' mathematics anxiety. This research focuses on analysis and description of students' mathematics anxiety level generally and its dominant domain and aspect. Qualitative research with case study strategy was used in this research. Subject in this research involved 15 students of 7th grade chosen with purposive sampling. Data in this research were students' mathematics anxiety scale result, interview record, and observation result during both mathematics learning activity and test. They were asked to complete mathematics anxiety scale before interviewed and observed. The results show that generally students' mathematics anxiety was identified in the moderate level. In addition, students' mathematics anxiety during mathematics test was identified in the high level, but it was in the moderate level during mathematics learning process. Based on the anxiety domain, students have a high mathematics anxiety on cognitive domain, while it was in the moderate level for psychological and physiological domains. On the other hand, it was identified in low level for psychological domain during mathematics learning process. Therefore, it can be concluded that students have serious and high anxiety regarding mathematics on the cognitive domain and mathematics test aspect.

Multi-modal classification of neurodegenerative disease by progressive graph-based transductive learning

PubMed Central

Wang, Zhengxia; Zhu, Xiaofeng; Adeli, Ehsan; Zhu, Yingying; Nie, Feiping; Munsell, Brent

2018-01-01

Graph-based transductive learning (GTL) is a powerful machine learning technique that is used when sufficient training data is not available. In particular, conventional GTL approaches first construct a fixed inter-subject relation graph that is based on similarities in voxel intensity values in the feature domain, which can then be used to propagate the known phenotype data (i.e., clinical scores and labels) from the training data to the testing data in the label domain. However, this type of graph is exclusively learned in the feature domain, and primarily due to outliers in the observed features, may not be optimal for label propagation in the label domain. To address this limitation, a progressive GTL (pGTL) method is proposed that gradually finds an intrinsic data representation that more accurately aligns imaging features with the phenotype data. In general, optimal feature-to-phenotype alignment is achieved using an iterative approach that: (1) refines inter-subject relationships observed in the feature domain by using the learned intrinsic data representation in the label domain, (2) updates the intrinsic data representation from the refined inter-subject relationships, and (3) verifies the intrinsic data representation on the training data to guarantee an optimal classification when applied to testing data. Additionally, the iterative approach is extended to multi-modal imaging data to further improve pGTL classification accuracy. Using Alzheimer’s disease and Parkinson’s disease study data, the classification accuracy of the proposed pGTL method is compared to several state-of-the-art classification methods, and the results show pGTL can more accurately identify subjects, even at different progression stages, in these two study data sets. PMID:28551556

An interactive learning environment for health care professionals.

PubMed Central

Cobbs, E.; Pincetl, P.; Silverman, B.; Liao, R. L.; Motta, C.

1994-01-01

This article summarizes experiences to date with building and deploying a clinical simulator that medical students use as part of a 3rd year primary care rotation. The simulated microworld helps students and health care professionals gain experience with and learn meta-cognitive skills for the care of complex patient populations that require treatment in the biopsychosocial-value dimensions. We explain lessons learned and next steps resulting from use of the program by over 300 users to date. PMID:7949975

38 CFR 21.7635 - Discontinuance dates.

Code of Federal Regulations, 2012 CFR

2012-07-01

...-Educational Assistance § 21.7635 Discontinuance dates. The effective date of reduction or discontinuance of... mitigating circumstances VA will terminate or reduce educational assistance effective the first date of the... practices of the institution of higher learning. (Authority: 10 U.S.C. 16136(b), 38 U.S.C. 3680(a); Pub. L...

38 CFR 21.7635 - Discontinuance dates.

Code of Federal Regulations, 2011 CFR

2011-07-01

...-Educational Assistance § 21.7635 Discontinuance dates. The effective date of reduction or discontinuance of... mitigating circumstances VA will terminate or reduce educational assistance effective the first date of the... practices of the institution of higher learning. (Authority: 10 U.S.C. 16136(b), 38 U.S.C. 3680(a); Pub. L...

38 CFR 21.7635 - Discontinuance dates.

Code of Federal Regulations, 2014 CFR

2014-07-01

...-Educational Assistance § 21.7635 Discontinuance dates. The effective date of reduction or discontinuance of... mitigating circumstances VA will terminate or reduce educational assistance effective the first date of the... practices of the institution of higher learning. (Authority: 10 U.S.C. 16136(b), 38 U.S.C. 3680(a); Pub. L...

38 CFR 21.7635 - Discontinuance dates.

Code of Federal Regulations, 2010 CFR

2010-07-01

...-Educational Assistance § 21.7635 Discontinuance dates. The effective date of reduction or discontinuance of... mitigating circumstances VA will terminate or reduce educational assistance effective the first date of the... practices of the institution of higher learning. (Authority: 10 U.S.C. 16136(b), 38 U.S.C. 3680(a); Pub. L...

38 CFR 21.7635 - Discontinuance dates.

Code of Federal Regulations, 2013 CFR

2013-07-01

...-Educational Assistance § 21.7635 Discontinuance dates. The effective date of reduction or discontinuance of... mitigating circumstances VA will terminate or reduce educational assistance effective the first date of the... practices of the institution of higher learning. (Authority: 10 U.S.C. 16136(b), 38 U.S.C. 3680(a); Pub. L...

Nondeclarative learning in children with specific language impairment: predicting regularities in the visuomotor, phonological, and cognitive domains.

PubMed

Mayor-Dubois, C; Zesiger, P; Van der Linden, M; Roulet-Perez, E

2014-01-01

Ullman (2004) suggested that Specific Language Impairment (SLI) results from a general procedural learning deficit. In order to test this hypothesis, we investigated children with SLI via procedural learning tasks exploring the verbal, motor, and cognitive domains. Results showed that compared with a Control Group, the children with SLI (a) were unable to learn a phonotactic learning task, (b) were able but less efficiently to learn a motor learning task and (c) succeeded in a cognitive learning task. Regarding the motor learning task (Serial Reaction Time Task), reaction times were longer and learning slower than in controls. The learning effect was not significant in children with an associated Developmental Coordination Disorder (DCD), and future studies should consider comorbid motor impairment in order to clarify whether impairments are related to the motor rather than the language disorder. Our results indicate that a phonotactic learning but not a cognitive procedural deficit underlies SLI, thus challenging Ullmans' general procedural deficit hypothesis, like a few other recent studies.

Beatquency domain and machine learning improve prediction of cardiovascular death after acute coronary syndrome.

PubMed

Liu, Yun; Scirica, Benjamin M; Stultz, Collin M; Guttag, John V

2016-10-06

Frequency domain measures of heart rate variability (HRV) are associated with adverse events after a myocardial infarction. However, patterns in the traditional frequency domain (measured in Hz, or cycles per second) may capture different cardiac phenomena at different heart rates. An alternative is to consider frequency with respect to heartbeats, or beatquency. We compared the use of frequency and beatquency domains to predict patient risk after an acute coronary syndrome. We then determined whether machine learning could further improve the predictive performance. We first evaluated the use of pre-defined frequency and beatquency bands in a clinical trial dataset (N = 2302) for the HRV risk measure LF/HF (the ratio of low frequency to high frequency power). Relative to frequency, beatquency improved the ability of LF/HF to predict cardiovascular death within one year (Area Under the Curve, or AUC, of 0.730 vs. 0.704, p < 0.001). Next, we used machine learning to learn frequency and beatquency bands with optimal predictive power, which further improved the AUC for beatquency to 0.753 (p < 0.001), but not for frequency. Results in additional validation datasets (N = 2255 and N = 765) were similar. Our results suggest that beatquency and machine learning provide valuable tools in physiological studies of HRV.

Paradoxical Way for Losers in a Dating Game

NASA Astrophysics Data System (ADS)

Arizmendi, C. M.

2007-05-01

We study the dating market decision problem in which men and women repeatedly go out on dates and learn about each other. We consider a model for the dating market that takes into account progressive mutual learning. This model consists of a repeated game in which agents gain an uncertain payoff from being matched with a particular person on the other side of the market in each time period. Players have a list of preferred partners on the other set. The players that reach higher rank levels on the other set preferences list have also higher probability to be accepted for dating. A question can be raised, as considered in this study: Can the less appreciated players do better? Two different kinds of dating game are combined "à la Parrondo" to foster the less attractive players. Optimism seems to be highly recommendable, especially for losers.

Internal Domains of Natural Porous Media Revealed: Critical Locations for Transport, Storage, and Chemical Reaction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zachara, John M.; Brantley, Susan L.; Chorover, Jon D.

2016-03-16

Internal pore domains exist within rocks, lithic fragments, subsurface sediments and soil aggregates. These domains, which we term internal domains in porous media (IDPM), contain a significant fraction of their porosity as nanopores, dominate the reactive surface area of diverse porous media types, and are important locations for chemical reactivity and hydrocarbon storage. Traditionally difficult to interrogate, advances in instrumentation and imaging methods are providing new insights on the physical structures and chemical attributes of IDPM. In this review we: discuss analytical methods to characterize IDPM, evaluate what has been learned about their size distributions, connectivity, and extended structures; determinemore » whether they exhibit unique chemical reactivity; and assess potential for their inclusion in reactive transport models. Three key findings are noteworthy. 1) A combination of methods now allows complete characterization of the porosity spectrum of natural materials and its connectivity; while imaging microscopies are providing three dimensional representations of the interconnected pore network. 2) Chemical reactivity in pores <10 nm is expected to be different from micro and macropores, yet research performed to date is inconclusive on the nature, direction, and magnitude of effect. 3) Existing continuum reactive transport models treat IDPM as a sub-grid feature with average, empirical, scale-dependent parameters; and are not formulated to include detailed information on pore networks. Overall we find that IDPM are key features controlling hydrocarbon release from shales in hydrofracking systems, organic matter stabilization and recalcitrance in soil, weathering and soil formation, and long term inorganic and organic contaminant behavior in the vadose zone and groundwater. We conclude with an assessment of impactful research opportunities to advance understanding of IDPM, and to incorporate their important effects in reactive transport models for improved environmental simulation and prediction.« less

Calibration and Data Efforts of the National Ecological Observatory Network (NEON) Airborne Observation Platform during its Engineering Development Phase

NASA Astrophysics Data System (ADS)

Adler, J.; Goulden, T.; Kampe, T. U.; Leisso, N.; Musinsky, J.

2014-12-01

The National Ecological Observatory Network (NEON) has collected airborne photographic, lidar, and imaging spectrometer data in 5 of 20 unique ecological climate regions (domains) within the United States. As part of its mission to detect and forecast ecological change at continental scales over multiple decades, NEON Airborne Observation Platform (AOP) will aerially survey the entire network of 60 core and re-locatable terrestrial sites annually, each of which are a minimum of 10km-by-10km in extent. The current effort encompasses three years of AOP engineering test flights; in 2017 NEON will transition to full operational status in all 20 domains. To date the total airborne data collected spans 34 Terabytes, and three of the five sampled domain's L1 data are publically available upon request. The large volume of current data, and the expected data collection over the remaining 15 domains, is challenging NEON's data distribution plans, backup capability, and data discovery processes. To provide the public with the highest quality data, calibration and validation efforts of the camera, lidar, and spectrometer L0 data are implemented to produce L1 datasets. Where available, the collected airborne measurements are validated against ground reference points and surfaces and adjusted for instrumentation and atmospheric effects. The imaging spectrometer data is spectrally and radiometrically corrected using NIST-traceable procedures. This presentation highlights three years of flight operation experiences including:1) Lessons learned on payload re-configuration, data extraction, data distribution, permitting requirements, flight planning, and operational procedures2) Lidar validation through control data comparisons collected at the Boulder Municipal Airport (KBDU), the site of NEON's new hangar facility3) Spectrometer calibration efforts, to include both the laboratory and ground observations

GeoSegmenter: A statistically learned Chinese word segmenter for the geoscience domain

NASA Astrophysics Data System (ADS)

Huang, Lan; Du, Youfu; Chen, Gongyang

2015-03-01

Unlike English, the Chinese language has no space between words. Segmenting texts into words, known as the Chinese word segmentation (CWS) problem, thus becomes a fundamental issue for processing Chinese documents and the first step in many text mining applications, including information retrieval, machine translation and knowledge acquisition. However, for the geoscience subject domain, the CWS problem remains unsolved. Although a generic segmenter can be applied to process geoscience documents, they lack the domain specific knowledge and consequently their segmentation accuracy drops dramatically. This motivated us to develop a segmenter specifically for the geoscience subject domain: the GeoSegmenter. We first proposed a generic two-step framework for domain specific CWS. Following this framework, we built GeoSegmenter using conditional random fields, a principled statistical framework for sequence learning. Specifically, GeoSegmenter first identifies general terms by using a generic baseline segmenter. Then it recognises geoscience terms by learning and applying a model that can transform the initial segmentation into the goal segmentation. Empirical experimental results on geoscience documents and benchmark datasets showed that GeoSegmenter could effectively recognise both geoscience terms and general terms.

Explicit Building-Block Multiobjective Genetic Algorithms: Theory, Analysis, and Development

DTIC Science & Technology

2003-03-01

Member Date Dr. (Maj) David A. Van Veldhuizen Committee Member Date Dr. Richard F. Deckro Dean’s Representative Date Accepted: Robert A. Calico, Jr...results in increased throughput and vice-versa. Van Veldhuizen validated the concept that BBs exist and are useful in the multiob- jective domain [184...extended to multiobjective functions. Van Veldhuizen states that BBs are not handled differently by MOEAs as compared to EAs. Even though an MOEA

An Examination of Multiple Intelligence Domains and Learning Styles of Pre-Service Mathematics Teachers: Their Reflections on Mathematics Education

ERIC Educational Resources Information Center

Ozgen, Kemal; Tataroglu, Berna; Alkan, Huseyin

2011-01-01

The present study aims to identify pre-service mathematics teachers' multiple intelligence domains and learning style profiles, and to establish relationships between them. Employing the survey model, the study was conducted with the participation of 243 pre-service mathematics teachers. The study used the "multiple intelligence domains…

Problems of Implementing SCORM in an Enterprise Distance Learning Architecture: SCORM Incompatibility across Multiple Web Domains.

ERIC Educational Resources Information Center

Engelbrecht, Jeffrey C.

2003-01-01

Delivering content to distant users located in dispersed networks, separated by firewalls and different web domains requires extensive customization and integration. This article outlines some of the problems of implementing the Sharable Content Object Reference Model (SCORM) in the Marine Corps' Distance Learning System (MarineNet) and extends…

Personal Reflection: Pedagogical Content Knowledge and the Affective Domain of Scholarship of Teaching and Learning

ERIC Educational Resources Information Center

Garritz, Andoni

2010-01-01

The question of these reflections is if among those content-dependent instructional conditions necessary to attain conceptual understanding, those belonging to the affective domain of teaching and learning must be included in Pedagogical Content Knowledge (PCK), the special amalgam of content knowledge and knowledge of general pedagogy that a…

When Global Structure "Explains Away" Local Grammar: A Bayesian Account of Rule-Induction in Tone Sequences

ERIC Educational Resources Information Center

Dawson, Colin; Gerken, LouAnn

2011-01-01

While many constraints on learning must be relatively experience-independent, past experience provides a rich source of guidance for subsequent learning. Discovering structure in some domain can inform a learner's future hypotheses about that domain. If a general property accounts for particular sub-patterns, a rational learner should not…

Pedagogically-Driven Ontology Network for Conceptualizing the e-Learning Assessment Domain

ERIC Educational Resources Information Center

Romero, Lucila; North, Matthew; Gutiérrez, Milagros; Caliusco, Laura

2015-01-01

The use of ontologies as tools to guide the generation, organization and personalization of e-learning content, including e-assessment, has drawn attention of the researchers because ontologies can represent the knowledge of a given domain and researchers use the ontology to reason about it. Although the use of these semantic technologies tends to…

Engaging Students to Learn through the Affective Domain: A New Framework for Teaching in the Geosciences

ERIC Educational Resources Information Center

van der Hoeven Kraft, Katrien J.; Srogi, LeeAnn; Husman, Jenefer; Semken, Steven; Fuhrman, Miriam

2011-01-01

To motivate student learning, the affective domain--emotion, attitude, and motivation--must be engaged. We propose a model that is specific to the geosciences with theoretical components of motivation and emotion from the field of educational psychology, and a term we are proposing, "connections with Earth" based on research in the…

Impact of Expectancy-Value and Situational Interest Motivation Specificity on Physical Education Outcomes

ERIC Educational Resources Information Center

Ding, Haiyong; Sun, Haichun; Chen, Ang

2013-01-01

To be successful in learning, students need to be motivated to engage and learn. The domain-specificity motivation theory articulates that student motivation is often determined by the content being taught to them. The purpose of this study was to extend the theory by determining domain-specificity of situational interest and expectancy-value…

Investigating the Potential of the Flipped Classroom Model in K-12 ICT Teaching and Learning: An Action Research Study

ERIC Educational Resources Information Center

Kostaris, Christoforos; Sergis, Stylianos; Sampson, Demetrios G.; Giannakos, Michail N.; Pelliccione, Lina

2017-01-01

The emerging Flipped Classroom approach has been widely used to enhance teaching practices in many subject domains and educational levels, reporting promising results for enhancing student learning experiences. However, despite this encouraging body of research, the subject domain of Information and Communication Technologies (ICT) teaching at…

Vineland-II adaptive behavior profile of children with attention-deficit/hyperactivity disorder or specific learning disorders.

PubMed

Balboni, Giulia; Incognito, Oriana; Belacchi, Carmen; Bonichini, Sabrina; Cubelli, Roberto

2017-02-01

The evaluation of adaptive behavior is informative in children with attention-deficit/hyperactivity disorder (ADHD) or specific learning disorders (SLD). However, the few investigations available have focused only on the gross level of domains of adaptive behavior. To investigate which item subsets of the Vineland-II can discriminate children with ADHD or SLD from peers with typical development. Student's t-tests, ROC analysis, logistic regression, and linear discriminant function analysis were used to compare 24 children with ADHD, 61 elementary students with SLD, and controls matched on age, sex, school level attended, and both parents' education level. Several item subsets that address not only ADHD core symptoms, but also understanding in social context and development of interpersonal relationships, allowed discrimination of children with ADHD from controls. The combination of four item subsets (Listening and attending, Expressing complex ideas, Social communication, and Following instructions) classified children with ADHD with both sensitivity and specificity of 87.5%. Only Reading skills, Writing skills, and Time and dates discriminated children with SLD from controls. Evaluation of Vineland-II scores at the level of item content categories is a useful procedure for an efficient clinical description. Copyright © 2016 Elsevier Ltd. All rights reserved.

Exploring the Conceptual Universe

ERIC Educational Resources Information Center

Kemp, Charles

2012-01-01

Humans can learn to organize many kinds of domains into categories, including real-world domains such as kinsfolk and synthetic domains such as sets of geometric figures that vary along several dimensions. Psychologists have studied many individual domains in detail, but there have been few attempts to characterize or explore the full space of…

Lifelong learning of Chinese rural physicians: preliminary psychometrics and influencing factors.

PubMed

Li, Honghe; Wang, Ziwei; Jiang, Nan; Liu, Yang; Wen, Deliang

2015-10-30

There are more than 4.9 million rural health workers undertaking the health care need of rural population of over 629 million in China. The lifelong learning of physicians is vital in maintaining up-to-date and qualified health care, but rural physicians in many developing countries lack adequate medical professional developments. There has also been no empirical research focused on the lifelong learning of rural physician populations. The purpose of this study was to investigate the primary levels of lifelong learning of the rural physicians and to analyze group differences. We conducted a cross-sectional study on 1197 rural physicians using the Jefferson Scale of Physician Lifelong Learning (JSPLL). Cronbach's α coefficient, exploratory factor analysis, independent sample t-test, and one-way ANOVA followed by Student-Newman-Keuls test were performed to analyze the data. For Chinese rural physicians, the JSPLL was reliable (Cronbach's α coefficient = 0.872) and valid, with exploratory factor analysis fitting a 3-factor model and accounting for a total of 60.46 % of the variance. The mean lifelong learning score was 45.56. Rural physicians generally performed worse in the technical skills in seeking information domain. Rural physicians with 21-30 working years have a lower score of lifelong learning (P < 0.05) than other phases of working years. Career satisfaction and professional titles had a significantly positive influence on physicians' orientation towards lifelong learning (P < 0.05). The overall lifelong learning scores of physicians who received more training after completion of medical school were higher than those with less additional post-medical school training (P <0.05). The JSPLL is effective for the Chinese rural physician population. In order to cope with impacting factors on rural physicians' lifelong learning, the results of the study reinforced the importance of continuing medical education and career satisfaction for lifelong learning and the need for medical schools and hospitals to provide reasonable strategies and necessary support for rural physicians with different amounts of working years. Providing rural physicians more educational opportunities and helping them access educational resources may be an effective strategy for improving their orientation to lifelong learning.

Philosophy of Healthcare Ethics Practice Statements: Quality Attestation and Beyond.

PubMed

Notini, Lauren

2018-06-13

One element of the American Society for Bioethics and Humanities' recently-piloted quality attestation portfolio for clinical ethics consultants is a "philosophy of clinical ethics consultation statement" describing the candidate's approach to clinical ethics consultation. To date, these statements have been under-explored in the literature, in contrast to philosophy statements in other fields such as academic teaching. In this article, I argue there is merit in expanding the content of these statements beyond clinical ethics consultation alone to describe the author's approach to other important "domains" of healthcare ethics practice (e.g., organizational policy development/review and ethics teaching). I also claim such statements have at least three additional uses outside quality attestation: (1) as a reflective practice learning tool to increase role clarity among practicing healthcare ethicists and bioethics fellows; (2) assisting practicing healthcare ethicists in clarifying role expectations with those they work with; and (3) helping inform developing professional practice standards.

SemanticOrganizer: A Customizable Semantic Repository for Distributed NASA Project Teams

NASA Technical Reports Server (NTRS)

Keller, Richard M.; Berrios, Daniel C.; Carvalho, Robert E.; Hall, David R.; Rich, Stephen J.; Sturken, Ian B.; Swanson, Keith J.; Wolfe, Shawn R.

2004-01-01

SemanticOrganizer is a collaborative knowledge management system designed to support distributed NASA projects, including diverse teams of scientists, engineers, and accident investigators. The system provides a customizable, semantically structured information repository that stores work products relevant to multiple projects of differing types. SemanticOrganizer is one of the earliest and largest semantic web applications deployed at NASA to date, and has been used in diverse contexts ranging from the investigation of Space Shuttle Columbia's accident to the search for life on other planets. Although the underlying repository employs a single unified ontology, access control and ontology customization mechanisms make the repository contents appear different for each project team. This paper describes SemanticOrganizer, its customization facilities, and a sampling of its applications. The paper also summarizes some key lessons learned from building and fielding a successful semantic web application across a wide-ranging set of domains with diverse users.

A Whale of a Tale: Creating Spacecraft Telemetry Data Analysis Products for the Deep Impact Mission

NASA Technical Reports Server (NTRS)

Sturdevant, Kathryn F.; Wright, Jesse J.; Lighty, Roger A.; Nakamura, Lori L.

2006-01-01

This paper describes some of the challenges and lessons learned from the Deep Impact (DI) Mission Ground Data System's (GDS) telemetry data processing and product generation tool, nicknamed 'Whale.' One of the challenges of any mission is to analyze testbed and operational telemetry data. Methods to retrieve this data to date have required spacecraft subsystem members to become experts in the use of a myriad of query and plot tools. As budgets shrink, and the GDS teams grow smaller, more of the burden to understand these tools falls on the users. The user base also varies from novice to expert, and requiring them to become GDS tool experts in addition to spacecraft domain experts is an undue burden. The "Whale" approach is to process all of the data for a given spacecraft test, and provide each subsystem with plots and data products 'automagically.'.

Expression and Purification of a Matrix Metalloprotease Transmembrane Domain in Escherichia coli.

PubMed

Galea, Charles A

2017-01-01

Membrane tethered matrix metalloproteases are bound to the plasma membrane by a glycosylphosphatidylinositol-anchor or a transmembrane domain. To date, most studies of membrane-bound matrix metalloprotease have focused on the globular catalytic and protein-protein interaction domains of these enzymes. However, the transmembrane domains have been poorly studied even though they are known to mediate intracellular signaling via interaction with various cellular proteins. The expression and purification of the transmembrane domain of these proteins can be challenging due to their hydrophobic nature. In this chapter we describe the purification of a transmembrane domain for a membrane-bound matrix metalloprotease expressed in E. coli and its initial characterization by NMR spectroscopy.

New Perspectives on Teaching and Working with Languages in the Digital Era

ERIC Educational Resources Information Center

Pareja-Lora, Antonio, Ed.; Calle-Martínez, Cristina, Ed.; Rodríguez-Arancón, Pilar, Ed.

2016-01-01

This volume offers a comprehensive, up-to-date, empirical and methodological view over the new scenarios and environments for language teaching and learning recently emerged (e.g. blended learning, e-learning, ubiquitous learning, social learning, autonomous learning or lifelong learning), and also over some of the new approaches to language…

The Case for Case-Based Transfer Learning

DTIC Science & Technology

2011-01-01

Thorndike and Woodworth 1901; Perkins and Salomon 1994; Bransford, Brown, and Cocking 2000), among other disciplines. Transfer learning uses knowledge...Transfer Learning for Rein- forcement Learning Domains: A Survey. Journal of Machine Learning Research 10(1): 1633–1685. Thorndike , E. L., and

Students Engaged in Learning

ERIC Educational Resources Information Center

Ismail, Emad A.; Groccia, James E.

2018-01-01

Engaging students in learning is a basic principle of effective undergraduate education. Outcomes of engaging students include meaningful learning experiences and enhanced skills in all learning domains. This chapter reviews the influence of engaging students in different forms of active learning on cognitive, psychomotor, and affective skill…

Dangerous Liaisons? Dating and Drinking Diffusion in Adolescent Peer Networks

ERIC Educational Resources Information Center

Kreager, Derek A.; Haynie, Dana L.

2011-01-01

The onset and escalation of alcohol consumption and romantic relationships are hallmarks of adolescence. Yet only recently have these domains jointly been the focus of sociological inquiry. We extend this literature by connecting alcohol use, dating, and peers to understand the diffusion of drinking behavior in school-based friendship networks.…

Emotional Factors that Influence Student Typewriting Behavior.

ERIC Educational Resources Information Center

Robinson, Jerry W.; Ownby, Arnola C.

1979-01-01

The authors discuss the cognitive, affective, and psychomotor domains of learning typewriting, student attitudes toward learning, their self-concept, and teacher attitudes toward student learning ability, with learning conditions and motivation techniques for effective typewriting instruction. (MF)

Support-vector-machine tree-based domain knowledge learning toward automated sports video classification

NASA Astrophysics Data System (ADS)

Xiao, Guoqiang; Jiang, Yang; Song, Gang; Jiang, Jianmin

2010-12-01

We propose a support-vector-machine (SVM) tree to hierarchically learn from domain knowledge represented by low-level features toward automatic classification of sports videos. The proposed SVM tree adopts a binary tree structure to exploit the nature of SVM's binary classification, where each internal node is a single SVM learning unit, and each external node represents the classified output type. Such a SVM tree presents a number of advantages, which include: 1. low computing cost; 2. integrated learning and classification while preserving individual SVM's learning strength; and 3. flexibility in both structure and learning modules, where different numbers of nodes and features can be added to address specific learning requirements, and various learning models can be added as individual nodes, such as neural networks, AdaBoost, hidden Markov models, dynamic Bayesian networks, etc. Experiments support that the proposed SVM tree achieves good performances in sports video classifications.

47 CFR 64.3100 - Restrictions on mobile service commercial messages.

Code of Federal Regulations, 2013 CFR

2013-10-01

... deliver goods or services, including product updates or upgrades, that the recipient is entitled to... wireless domain names list. CMRS providers must: (1) File any future updates to listings with the... on the list or last date of use; and (3) Certify that any domain name placed on the FCC's wireless...

47 CFR 64.3100 - Restrictions on mobile service commercial messages.

Code of Federal Regulations, 2012 CFR

2012-10-01

... deliver goods or services, including product updates or upgrades, that the recipient is entitled to... wireless domain names list. CMRS providers must: (1) File any future updates to listings with the... on the list or last date of use; and (3) Certify that any domain name placed on the FCC's wireless...

47 CFR 64.3100 - Restrictions on mobile service commercial messages.

Code of Federal Regulations, 2014 CFR

2014-10-01

... deliver goods or services, including product updates or upgrades, that the recipient is entitled to... wireless domain names list. CMRS providers must: (1) File any future updates to listings with the... on the list or last date of use; and (3) Certify that any domain name placed on the FCC's wireless...

From opening to subduction of an oceanic domain constrained by LA-ICP-MS U-Pb zircon dating (Variscan belt, Southern Armorican Massif, France)

NASA Astrophysics Data System (ADS)

Paquette, J.-L.; Ballèvre, M.; Peucat, J.-J.; Cornen, G.

2017-12-01

In the Variscan belt of Western Europe, the lifetime and evolution of the oceanic domain is poorly constrained by sparse, outdated and unreliable multigrain ID-TIMS U-Pb zircon dating. In this article, we present a complete in situ LA-ICP-MS dataset of about 300 U-Pb zircon analyses obtained on most of the ophiolitic and eclogitic outcrops of Southern Brittany, comprising new dating of previously published zircon populations and newly discovered rock samples. In situ dating and cathodo-luminescence imaging of each zircon grain yields new absolute time-constraints on the evolution of the Galicia-Moldanubian Ocean. The new results confirm that the opening of this oceanic domain is well defined at about 490 Ma. In contrast, the generally-quoted 400-410 Ma-age for the high-pressure event related to the subduction of the oceanic crust is definitely not recorded in the zircons of the eclogites. In light of these new data, we propose that the obduction of oceanic rocks occurred at about 370-380 Ma while the high-pressure event is recorded at 355 Ma in only a few zircon grains of some eclogite samples. Additionally, this large scale dating project demonstrates that the zircons from eclogites do not systematically recrystallise during the high pressure event and consequently their U-Pb systems do not record that metamorphism systematically. These zircons rather preserve the isotopic memory of the magmatic crystallization of their igneous protolith. Another example of an eclogite sample from the French Massif Central illustrates the frequent mistake in the interpretation of the ages of the early hydrothermal alteration of zircons in the oceanic crust versus partial or complete recrystallization during eclogite facies metamorphism.

Inter- and Intra-Dimensional Dependencies in Implicit Phonotactic Learning

ERIC Educational Resources Information Center

Moreton, Elliott

2012-01-01

Is phonological learning subject to the same inductive biases as learning in other domains? Previous studies of non-linguistic learning found that intra-dimensional dependencies (between two instances of the same feature) were learned more easily than inter-dimensional ones. This study compares implicit learning of intra- and inter-dimensional…

Girls Health

MedlinePlus

... how to stay safe anywhere. Learn more Strong body, healthy mind. Thirteen ways being fit helps you. Learn more Mental health matters. Learn ways to cope if you’re feeling sad. Learn more Spotlight: Jaelin ... your body or your period? Confused about dating or friendships? ...

Information Pre-Processing using Domain Meta-Ontology and Rule Learning System

NASA Astrophysics Data System (ADS)

Ranganathan, Girish R.; Biletskiy, Yevgen

Around the globe, extraordinary amounts of documents are being created by Enterprises and by users outside these Enterprises. The documents created in the Enterprises constitute the main focus of the present chapter. These documents are used to perform numerous amounts of machine processing. While using thesedocuments for machine processing, lack of semantics of the information in these documents may cause misinterpretation of the information, thereby inhibiting the productiveness of computer assisted analytical work. Hence, it would be profitable to the Enterprises if they use well defined domain ontologies which will serve as rich source(s) of semantics for the information in the documents. These domain ontologies can be created manually, semi-automatically or fully automatically. The focus of this chapter is to propose an intermediate solution which will enable relatively easy creation of these domain ontologies. The process of extracting and capturing domain ontologies from these voluminous documents requires extensive involvement of domain experts and application of methods of ontology learning that are substantially labor intensive; therefore, some intermediate solutions which would assist in capturing domain ontologies must be developed. This chapter proposes a solution in this direction which involves building a meta-ontology that will serve as an intermediate information source for the main domain ontology. This chapter proposes a solution in this direction which involves building a meta-ontology as a rapid approach in conceptualizing a domain of interest from huge amount of source documents. This meta-ontology can be populated by ontological concepts, attributes and relations from documents, and then refined in order to form better domain ontology either through automatic ontology learning methods or some other relevant ontology building approach.

Mental health and health-related quality of life of Chinese college students who were the victims of dating violence.

PubMed

Choi, Edmond P H; Wong, Janet Y H; Fong, Daniel Y T

2017-04-01

The aim of the study is to evaluate the mental health and health-related quality of life (HRQOL) of Chinese college students who were the victims of dating violence. Six hundred and fifty-two subjects were included in the data analysis. Subjects completed a structured questionnaire containing the Woman Abuse Screening tool, the Hospital Anxiety and Depression Scale, the 10-item version of the Perceived Stress Scale (PSS-10) and the World Health Organization Quality of Life-BREF Instrument (WHOQOL-BREF). Analysis by independent t test suggested that victims of dating violence had more severe depressive, anxiety and stress symptoms and poorer HRQOL than non-victims. Multiple linear regression models found that more severe dating violence victimization was associated with more severe depressive, anxiety and stress symptoms. The mediation analysis found that after simultaneously controlling for the degree of depressive, anxiety and stress symptoms, the direct effect between dating violence severity and HRQOL, as measured by overall HRQOL and the global health, physical and environment domains of the WHOQOL-BREF, was statistically insignificant, supporting a full-mediation model. The relationship between dating violence severity and the social domain of HRQOL was partially mediated by the degree of depressive, anxiety and stress symptoms. Victims of dating violence had poorer mental health and HRQOL than non-victims. The study findings affirm the importance of assessing depressive, anxiety and stress symptoms in victims and the need to improve their depressive, anxiety and stress symptoms to diminish the negative effects of dating violence, which are apparent in their HRQOL.

What Is Learned when Concept Learning Fails?--A Theory of Restricted-Domain Relational Learning

ERIC Educational Resources Information Center

Wright, Anthony A.; Lickteig, Mark T.

2010-01-01

Two matching-to-sample (MTS) and four same/different (S/D) experiments employed tests to distinguish between item-specific learning and relational learning. One MTS experiment showed item-specific learning when concept learning failed (i.e., no novel-stimulus transfer). Another MTS experiment showed item-specific learning when pigeons'…

A case for restricted-domain relational learning.

PubMed

Wright, Anthony A; Katz, Jeffrey S

2009-10-01

Monkeys and pigeons learned a same/different task with pairs that were selected from a training set of eight picture stimuli. They showed no novel-stimulus transfer and hence no abstract-concept learning. They were also tested with novel pairs of the eight training pictures (i.e., combinations that had not been used in training) and with inverted pictures of the training pairs. If the subjects had learned the task item-specifically (e.g., if-then or configural learning), they should have failed these tests, but they performed well with novel combinations of training pictures and inverted pictures, suggesting that they learned the task relationally (i.e., on the basis of the relationship between the two pictures that were presented in each trial). This somewhat paradoxical conclusion of relational learning in the absence of abstract-concept learning is contrary to most theories of abstract-concept learning. The implications of this conclusion are discussed in the context of restricted-domain relational learning.

Friendship Predictors of Global Self-Worth and Domain-Specific Self-Concepts in University Students with and without Learning Disability

ERIC Educational Resources Information Center

Shany, Michal; Wiener, Judith; Assido, Michal

2013-01-01

This study investigated the association among friendship, global self-worth, and domain-specific self-concepts in 102 university students with and without learning disabilities (LD). Students with LD reported lower global self-worth and academic self-concept than students without LD, and this difference was greater for women. Students with LD also…

Primary School Teachers' Practices and Troubles with the Students Who They Think Have Undiagnosed Difficulties in Verbal Communication, Reading and Writing

ERIC Educational Resources Information Center

Ergen, Yusuf; Elma, Cevat

2018-01-01

The primary school Turkish program was basically built on three learning domains. These are the learning domains of verbal communication, reading and writing. The purpose of the present study is to determine primary school teachers' practices and difficulties related to students considered to have undiognosed verbal communication, reading and…

The Relation between Cognitive and Metacognitive Processing: Building Bridges between the SRL, MDL, and SAL Domains

ERIC Educational Resources Information Center

Coertjens, Liesje

2018-01-01

Aim: The main aim of this commentary was to connect the insights from the contributions of the special issue on the intersection between depth and the regulation of strategy use. The seven contributions in this special issue stem from three perspectives: self-regulated learning (SRL), model of domain learning (MDL), or the student approaches to…

The Moderating Role of Non-Controlling Supervision and Organizational Learning Culture on Employee Creativity: The Influences of Domain Expertise and Creative Personality

ERIC Educational Resources Information Center

Jeong, Shinhee; McLean, Gary N.; McLean, Laird D.; Yoo, Sangok; Bartlett, Kenneth

2017-01-01

Purpose: By adopting a multilevel approach, this paper aims to examine the relationships among employee creativity and creative personality, domain expertise (i.e. individual-level factors), non-controlling supervision style and organizational learning culture (i.e. team-level factors). It also investigates the cross-level interactions between…

Using a Delphi Technique to Seek Consensus Regarding Definitions, Descriptions and Classification of Terms Related to Implicit and Explicit Forms of Motor Learning

PubMed Central

Kleynen, Melanie; Braun, Susy M.; Bleijlevens, Michel H.; Lexis, Monique A.; Rasquin, Sascha M.; Halfens, Jos; Wilson, Mark R.; Beurskens, Anna J.; Masters, Rich S. W.

2014-01-01

Background Motor learning is central to domains such as sports and rehabilitation; however, often terminologies are insufficiently uniform to allow effective sharing of experience or translation of knowledge. A study using a Delphi technique was conducted to ascertain level of agreement between experts from different motor learning domains (i.e., therapists, coaches, researchers) with respect to definitions and descriptions of a fundamental conceptual distinction within motor learning, namely implicit and explicit motor learning. Methods A Delphi technique was embedded in multiple rounds of a survey designed to collect and aggregate informed opinions of 49 international respondents with expertise related to motor learning. The survey was administered via an online survey program and accompanied by feedback after each round. Consensus was considered to be reached if ≥70% of the experts agreed on a topic. Results Consensus was reached with respect to definitions of implicit and explicit motor learning, and seven common primary intervention strategies were identified in the context of implicit and explicit motor learning. Consensus was not reached with respect to whether the strategies promote implicit or explicit forms of learning. Discussion The definitions and descriptions agreed upon may aid translation and transfer of knowledge between domains in the field of motor learning. Empirical and clinical research is required to confirm the accuracy of the definitions and to explore the feasibility of the strategies that were identified in research, everyday practice and education. PMID:24968228

Development of Dual-Retrieval Processes in Recall: Learning, Forgetting, and Reminiscence

PubMed Central

Brainerd, C. J.; Aydin, C.; Reyna, V. F.

2012-01-01

We investigated the development of dual-retrieval processes with a low-burden paradigm that is suitable for research with children and neurocognitively impaired populations (e.g., older adults with mild cognitive impairment or dementia). Rich quantitative information can be obtained about recollection, reconstruction, and familiarity judgment by defining a Markov model over simple recall tasks like those that are used in clinical neuropsychology batteries. The model measures these processes separately for learning, forgetting, and reminiscence. We implemented this procedure in some developmental experiments, whose aims were (a) to measure age changes in recollective and nonrecollective retrieval during learning, forgetting, and reminiscence and (b) to measure age changes in content dimensions (e.g., taxonomic relatedness) that affect the two forms of retrieval. The model provided excellent fits in all three domains. Concerning (a), recollection, reconstruction, and familiarity judgment all improved during the child-to-adolescent age range in the learning domain, whereas only recollection improved in the forgetting domain, and the processes were age-invariant in the reminiscence domain. Concerning (b), although some elements of the adult pattern of taxonomic relatedness effects were detected by early adolescence, the adult pattern differs qualitatively from corresponding patterns in children and adolescents. PMID:22778491

Systematic Design of a Learning Environment for Domain-Specific and Domain-General Critical Thinking Skills

ERIC Educational Resources Information Center

Tiruneh, Dawit Tibebu; Weldeslassie, Ataklti G.; Kassa, Abrham; Tefera, Zinaye; De Cock, Mieke; Elen, Jan

2016-01-01

Identifying effective instructional approaches that stimulate students' critical thinking (CT) has been the focus of a large body of empirical research. However, there is little agreement on the instructional principles and procedures that are theoretically sound and empirically valid to developing both domain-specific and domain-general CT…

"Decisions, decisions, decisions": transfer and specificity of decision-making skill between sports.

PubMed

Causer, Joe; Ford, Paul R

2014-08-01

The concept of transfer of learning holds that previous practice or experience in one task or domain will enable successful performance in another related task or domain. In contrast, specificity of learning holds that previous practice or experience in one task or domain does not transfer to other related tasks or domains. The aim of the current study is to examine whether decision-making skill transfers between sports that share similar elements, or whether it is specific to a sport. Participants (n = 205) completed a video-based temporal occlusion decision-making test in which they were required to decide on which action to execute across a series of 4 versus 4 soccer game situations. A sport engagement questionnaire was used to identify 106 soccer players, 43 other invasion sport players and 58 other sport players. Positive transfer of decision-making skill occurred between soccer and other invasion sports, which are related and have similar elements, but not from volleyball, supporting the concept of transfer of learning.

In search of periodic signatures in IGS REPRO1 solution

NASA Astrophysics Data System (ADS)

Mtamakaya, J. D.; Santos, M. C.; Craymer, M. R.

2010-12-01

We have been looking for periodic signatures in the REPRO1 solution recently released by the IGS. At this stage, a selected sub-set of IGS station time series in position and residual domain are under harmonic analysis. We can learn different things from this analysis. From the position domain, we can learn more about actual station motions. From the residual domain, we can learn more about mis-modelled or un-modelled errors. As far as error sources are concerned, we have investigated effects that may be due to tides, atmospheric loading, definition of the position of the figure axis and GPS constellation geometry. This poster presents and discusses our findings and presents insights on errors that need to be modelled or have their models improved.

Mining and Utilizing Dataset Relevancy from Oceanographic Dataset (MUDROD) Metadata, Usage Metrics, and User Feedback to Improve Data Discovery and Access

NASA Astrophysics Data System (ADS)

Li, Y.; Jiang, Y.; Yang, C. P.; Armstrong, E. M.; Huang, T.; Moroni, D. F.; McGibbney, L. J.

2016-12-01

Big oceanographic data have been produced, archived and made available online, but finding the right data for scientific research and application development is still a significant challenge. A long-standing problem in data discovery is how to find the interrelationships between keywords and data, as well as the intrarelationships of the two individually. Most previous research attempted to solve this problem by building domain-specific ontology either manually or through automatic machine learning techniques. The former is costly, labor intensive and hard to keep up-to-date, while the latter is prone to noise and may be difficult for human to understand. Large-scale user behavior data modelling represents a largely untapped, unique, and valuable source for discovering semantic relationships among domain-specific vocabulary. In this article, we propose a search engine framework for mining and utilizing dataset relevancy from oceanographic dataset metadata, user behaviors, and existing ontology. The objective is to improve discovery accuracy of oceanographic data and reduce time for scientist to discover, download and reformat data for their projects. Experiments and a search example show that the proposed search engine helps both scientists and general users search with better ranking results, recommendation, and ontology navigation.

USI: a fast and accurate approach for conceptual document annotation.

PubMed

Fiorini, Nicolas; Ranwez, Sylvie; Montmain, Jacky; Ranwez, Vincent

2015-03-14

Semantic approaches such as concept-based information retrieval rely on a corpus in which resources are indexed by concepts belonging to a domain ontology. In order to keep such applications up-to-date, new entities need to be frequently annotated to enrich the corpus. However, this task is time-consuming and requires a high-level of expertise in both the domain and the related ontology. Different strategies have thus been proposed to ease this indexing process, each one taking advantage from the features of the document. In this paper we present USI (User-oriented Semantic Indexer), a fast and intuitive method for indexing tasks. We introduce a solution to suggest a conceptual annotation for new entities based on related already indexed documents. Our results, compared to those obtained by previous authors using the MeSH thesaurus and a dataset of biomedical papers, show that the method surpasses text-specific methods in terms of both quality and speed. Evaluations are done via usual metrics and semantic similarity. By only relying on neighbor documents, the User-oriented Semantic Indexer does not need a representative learning set. Yet, it provides better results than the other approaches by giving a consistent annotation scored with a global criterion - instead of one score per concept.

Learn About Sarcoidosis

MedlinePlus

... each(function(i){ var city = $(this).find('city').text(); var state = $(this).find('state').text(); var date = $(this).find('date').text(); if ((city != "") && (state != "")){ var citystate = ' | ' + city + ', ' + state; } else ...

Learn About Silicosis

MedlinePlus

... each(function(i){ var city = $(this).find('city').text(); var state = $(this).find('state').text(); var date = $(this).find('date').text(); if ((city != "") && (state != "")){ var citystate = ' | ' + city + ', ' + state; } else ...

Learn About Tuberculosis

MedlinePlus

... each(function(i){ var city = $(this).find('city').text(); var state = $(this).find('state').text(); var date = $(this).find('date').text(); if ((city != "") && (state != "")){ var citystate = ' | ' + city + ', ' + state; } else ...

A Pilot Study of Biomedical Text Comprehension using an Attention-Based Deep Neural Reader: Design and Experimental Analysis

PubMed Central

Lee, Kyubum; Kim, Byounggun; Jeon, Minji; Kim, Jihye; Tan, Aik Choon

2018-01-01

Background With the development of artificial intelligence (AI) technology centered on deep-learning, the computer has evolved to a point where it can read a given text and answer a question based on the context of the text. Such a specific task is known as the task of machine comprehension. Existing machine comprehension tasks mostly use datasets of general texts, such as news articles or elementary school-level storybooks. However, no attempt has been made to determine whether an up-to-date deep learning-based machine comprehension model can also process scientific literature containing expert-level knowledge, especially in the biomedical domain. Objective This study aims to investigate whether a machine comprehension model can process biomedical articles as well as general texts. Since there is no dataset for the biomedical literature comprehension task, our work includes generating a large-scale question answering dataset using PubMed and manually evaluating the generated dataset. Methods We present an attention-based deep neural model tailored to the biomedical domain. To further enhance the performance of our model, we used a pretrained word vector and biomedical entity type embedding. We also developed an ensemble method of combining the results of several independent models to reduce the variance of the answers from the models. Results The experimental results showed that our proposed deep neural network model outperformed the baseline model by more than 7% on the new dataset. We also evaluated human performance on the new dataset. The human evaluation result showed that our deep neural model outperformed humans in comprehension by 22% on average. Conclusions In this work, we introduced a new task of machine comprehension in the biomedical domain using a deep neural model. Since there was no large-scale dataset for training deep neural models in the biomedical domain, we created the new cloze-style datasets Biomedical Knowledge Comprehension Title (BMKC_T) and Biomedical Knowledge Comprehension Last Sentence (BMKC_LS) (together referred to as BioMedical Knowledge Comprehension) using the PubMed corpus. The experimental results showed that the performance of our model is much higher than that of humans. We observed that our model performed consistently better regardless of the degree of difficulty of a text, whereas humans have difficulty when performing biomedical literature comprehension tasks that require expert level knowledge. PMID:29305341

29 CFR 520.408 - What is the subminimum wage for learners and what must I do to comply with the terms of my...

Code of Federal Regulations, 2013 CFR

2013-07-01

... day; (3) The occupations in which learners may be employed; (4) The authorized learning period of not... effective and expiration dates of the certificate. (b) Learners properly hired prior to the date on which a... their authorized learning period under the terms of the certificate, even though the certificate may...

29 CFR 520.408 - What is the subminimum wage for learners and what must I do to comply with the terms of my...

Code of Federal Regulations, 2014 CFR

2014-07-01

... day; (3) The occupations in which learners may be employed; (4) The authorized learning period of not... effective and expiration dates of the certificate. (b) Learners properly hired prior to the date on which a... their authorized learning period under the terms of the certificate, even though the certificate may...

29 CFR 520.408 - What is the subminimum wage for learners and what must I do to comply with the terms of my...

Code of Federal Regulations, 2012 CFR

2012-07-01

... day; (3) The occupations in which learners may be employed; (4) The authorized learning period of not... effective and expiration dates of the certificate. (b) Learners properly hired prior to the date on which a... their authorized learning period under the terms of the certificate, even though the certificate may...

29 CFR 520.408 - What is the subminimum wage for learners and what must I do to comply with the terms of my...

Code of Federal Regulations, 2011 CFR

2011-07-01

... day; (3) The occupations in which learners may be employed; (4) The authorized learning period of not... effective and expiration dates of the certificate. (b) Learners properly hired prior to the date on which a... their authorized learning period under the terms of the certificate, even though the certificate may...

Structure-function analysis of the auxilin J-domain reveals an extended Hsc70 interaction interface.

PubMed

Jiang, Jianwen; Taylor, Alexander B; Prasad, Kondury; Ishikawa-Brush, Yumiko; Hart, P John; Lafer, Eileen M; Sousa, Rui

2003-05-20

J-domains are widespread protein interaction modules involved in recruiting and stimulating the activity of Hsp70 family chaperones. We have determined the crystal structure of the J-domain of auxilin, a protein which is involved in uncoating clathrin-coated vesicles. Comparison to the known structures of J-domains from four other proteins reveals that the auxilin J-domain is the most divergent of all J-domain structures described to date. In addition to the canonical J-domain features described previously, the auxilin J-domain contains an extra N-terminal helix and a long loop inserted between helices I and II. The latter loop extends the positively charged surface which forms the Hsc70 binding site, and is shown by directed mutagenesis and surface plasmon resonance to contain side chains important for binding to Hsc70.

Hypermedia in Vocational Learning: A Hypermedia Learning Environment for Training Management Skills

ERIC Educational Resources Information Center

Konradt, Udo

2004-01-01

A learning environment is defined as an arrangement of issues, methods, techniques, and media in a given domain. Besides temporal and spatial features a learning environment considers the social situation in which learning takes place. In (hypermedia) learning environments the concept of exploration and the active role of the learner is…

The Nature of Student Teachers' Regulation of Learning in Teacher Education

ERIC Educational Resources Information Center

Endedijk, Maaike D.; Vermunt, Jan D.; Verloop, Nico; Brekelmans, Mieke

2012-01-01

Background: Self-regulated learning (SRL) has mainly been conceptualized to involve student learning within academic settings. In teacher education, where learning from theory and practice is combined, student teachers also need to regulate their learning. Hence, there is an urgent need to extend SRL theories to the domain of teacher learning and…

The Learning Healthcare System and Cardiovascular Care: A Scientific Statement From the American Heart Association.

PubMed

Maddox, Thomas M; Albert, Nancy M; Borden, William B; Curtis, Lesley H; Ferguson, T Bruce; Kao, David P; Marcus, Gregory M; Peterson, Eric D; Redberg, Rita; Rumsfeld, John S; Shah, Nilay D; Tcheng, James E

2017-04-04

The learning healthcare system uses health information technology and the health data infrastructure to apply scientific evidence at the point of clinical care while simultaneously collecting insights from that care to promote innovation in optimal healthcare delivery and to fuel new scientific discovery. To achieve these goals, the learning healthcare system requires systematic redesign of the current healthcare system, focusing on 4 major domains: science and informatics, patient-clinician partnerships, incentives, and development of a continuous learning culture. This scientific statement provides an overview of how these learning healthcare system domains can be realized in cardiovascular disease care. Current cardiovascular disease care innovations in informatics, data uses, patient engagement, continuous learning culture, and incentives are profiled. In addition, recommendations for next steps for the development of a learning healthcare system in cardiovascular care are presented. © 2017 American Heart Association, Inc.

Domain general learning: Infants use social and non-social cues when learning object statistics

PubMed Central

Barry, Ryan A.; Graf Estes, Katharine; Rivera, Susan M.

2015-01-01

Previous research has shown that infants can learn from social cues. But is a social cue more effective at directing learning than a non-social cue? This study investigated whether 9-month-old infants (N = 55) could learn a visual statistical regularity in the presence of a distracting visual sequence when attention was directed by either a social cue (a person) or a non-social cue (a rectangle). The results show that both social and non-social cues can guide infants’ attention to a visual shape sequence (and away from a distracting sequence). The social cue more effectively directed attention than the non-social cue during the familiarization phase, but the social cue did not result in significantly stronger learning than the non-social cue. The findings suggest that domain general attention mechanisms allow for the comparable learning seen in both conditions. PMID:25999879

Students' perception of the learning environment in a distributed medical programme.

PubMed

Veerapen, Kiran; McAleer, Sean

2010-09-24

The learning environment of a medical school has a significant impact on students' achievements and learning outcomes. The importance of equitable learning environments across programme sites is implicit in distributed undergraduate medical programmes being developed and implemented. To study the learning environment and its equity across two classes and three geographically separate sites of a distributed medical programme at the University of British Columbia Medical School that commenced in 2004. The validated Dundee Ready Educational Environment Survey was sent to all students in their 2nd and 3rd year (classes graduating in 2009 and 2008) of the programme. The domains of the learning environment surveyed were: students' perceptions of learning, students' perceptions of teachers, students' academic self-perceptions, students' perceptions of the atmosphere, and students' social self-perceptions. Mean scores, frequency distribution of responses, and inter- and intrasite differences were calculated. The perception of the global learning environment at all sites was more positive than negative. It was characterised by a strongly positive perception of teachers. The work load and emphasis on factual learning were perceived negatively. Intersite differences within domains of the learning environment were more evident in the pioneer class (2008) of the programme. Intersite differences consistent across classes were largely related to on-site support for students. Shared strengths and weaknesses in the learning environment at UBC sites were evident in areas that were managed by the parent institution, such as the attributes of shared faculty and curriculum. A greater divergence in the perception of the learning environment was found in domains dependent on local arrangements and social factors that are less amenable to central regulation. This study underlines the need for ongoing comparative evaluation of the learning environment at the distributed sites and interaction between leaders of these sites.

Ranking Medical Terms to Support Expansion of Lay Language Resources for Patient Comprehension of Electronic Health Record Notes: Adapted Distant Supervision Approach

PubMed Central

Jagannatha, Abhyuday N; Fodeh, Samah J; Yu, Hong

2017-01-01

Background Medical terms are a major obstacle for patients to comprehend their electronic health record (EHR) notes. Clinical natural language processing (NLP) systems that link EHR terms to lay terms or definitions allow patients to easily access helpful information when reading through their EHR notes, and have shown to improve patient EHR comprehension. However, high-quality lay language resources for EHR terms are very limited in the public domain. Because expanding and curating such a resource is a costly process, it is beneficial and even necessary to identify terms important for patient EHR comprehension first. Objective We aimed to develop an NLP system, called adapted distant supervision (ADS), to rank candidate terms mined from EHR corpora. We will give EHR terms ranked as high by ADS a higher priority for lay language annotation—that is, creating lay definitions for these terms. Methods Adapted distant supervision uses distant supervision from consumer health vocabulary and transfer learning to adapt itself to solve the problem of ranking EHR terms in the target domain. We investigated 2 state-of-the-art transfer learning algorithms (ie, feature space augmentation and supervised distant supervision) and designed 5 types of learning features, including distributed word representations learned from large EHR data for ADS. For evaluating ADS, we asked domain experts to annotate 6038 candidate terms as important or nonimportant for EHR comprehension. We then randomly divided these data into the target-domain training data (1000 examples) and the evaluation data (5038 examples). We compared ADS with 2 strong baselines, including standard supervised learning, on the evaluation data. Results The ADS system using feature space augmentation achieved the best average precision, 0.850, on the evaluation set when using 1000 target-domain training examples. The ADS system using supervised distant supervision achieved the best average precision, 0.819, on the evaluation set when using only 100 target-domain training examples. The 2 ADS systems both performed significantly better than the baseline systems (P<.001 for all measures and all conditions). Using a rich set of learning features contributed to ADS’s performance substantially. Conclusions ADS can effectively rank terms mined from EHRs. Transfer learning improved ADS’s performance even with a small number of target-domain training examples. EHR terms prioritized by ADS were used to expand a lay language resource that supports patient EHR comprehension. The top 10,000 EHR terms ranked by ADS are available upon request. PMID:29089288

Diet rich in date palm fruits improves memory, learning and reduces beta amyloid in transgenic mouse model of Alzheimer's disease.

PubMed

Subash, Selvaraju; Essa, Musthafa Mohamed; Braidy, Nady; Awlad-Thani, Kathyia; Vaishnav, Ragini; Al-Adawi, Samir; Al-Asmi, Abdullah; Guillemin, Gilles J

2015-01-01

At present, the treatment options available to delay the onset or slow down the progression of Alzheimer's disease (AD) are not effective. Recent studies have suggested that diet and lifestyle factors may represent protective strategies to minimize the risk of developing AD. Date palm fruits are a good source of dietary fiber and are rich in total phenolics and natural antioxidants, such as anthocyanins, ferulic acid, protocatechuic acid and caffeic acid. These polyphenolic compounds have been shown to be neuroprotective in different model systems. We investigated whether dietary supplementation with 2% and 4% date palm fruits (grown in Oman) could reduce cognitive and behavioral deficits in a transgenic mouse model for AD (amyloid precursor protein [APPsw]/Tg2576). The experimental groups of APP-transgenic mice from the age of 4 months were fed custom-mix diets (pellets) containing 2% and 4% date fruits. We assessed spatial memory and learning ability, psychomotor coordination, and anxiety-related behavior in all the animals at the age of 4 months and after 14 months of treatment using the Morris water maze test, rota-rod test, elevated plus maze test, and open-field test. We have also analyzed the levels of amyloid beta (Aβ) protein (1-40 and 1-42) in plasma of control and experimental animals. Standard diet-fed Tg mice showed significant memory deficits, increased anxiety-related behavior, and severe impairment in spatial learning ability, position discrimination learning ability and motor coordination when compared to wild-type on the same diet and Tg mice fed 2% and 4% date supplementation at the age of 18 months. The levels of both Aβ proteins were significantly lowered in date fruits supplemented groups than the Tg mice without the diet supplement. The neuroprotective effect offered by 4% date fruits diet to AD mice is higher than 2% date fruits diet. Our results suggest that date fruits dietary supplementation may have beneficial effects in lowering the risk, delaying the onset or slowing down the progression of AD.

Facilitation of learning: part 2.

PubMed

Warburton, Tyler; Houghton, Trish; Barry, Debbie

2016-04-27

The previous article in this series of 11, Facilitation of learning: part 1, reviewed learning theories and how they relate to clinical practice. Developing an understanding of these theories is essential for mentors and practice teachers to enable them to deliver evidence-based learning support. This is important given that effective learning support is dependent on an educator who possesses knowledge of their specialist area as well as the relevent tools and methods to support learning. The second domain of the Nursing and Midwifery Council's Standards to Support Learning and Assessment in Practice relates to the facilitation of learning. To fulfil this domain, mentors and practice teachers are required to demonstrate their ability to recognise the needs of learners and provide appropriate support to meet those needs. This article expands on some of the discussions from part 1 of this article and considers these from a practical perspective, in addition to introducing some of the tools that can be used to support learning.

Incremental learning of skill collections based on intrinsic motivation

PubMed Central

Metzen, Jan H.; Kirchner, Frank

2013-01-01

Life-long learning of reusable, versatile skills is a key prerequisite for embodied agents that act in a complex, dynamic environment and are faced with different tasks over their lifetime. We address the question of how an agent can learn useful skills efficiently during a developmental period, i.e., when no task is imposed on him and no external reward signal is provided. Learning of skills in a developmental period needs to be incremental and self-motivated. We propose a new incremental, task-independent skill discovery approach that is suited for continuous domains. Furthermore, the agent learns specific skills based on intrinsic motivation mechanisms that determine on which skills learning is focused at a given point in time. We evaluate the approach in a reinforcement learning setup in two continuous domains with complex dynamics. We show that an intrinsically motivated, skill learning agent outperforms an agent which learns task solutions from scratch. Furthermore, we compare different intrinsic motivation mechanisms and how efficiently they make use of the agent's developmental period. PMID:23898265

The quaternary architecture of RARβ–RXRα heterodimer facilitates domain–domain signal transmission

DOE PAGES

Chandra, Vikas; Wu, Dalei; Li, Sheng; ...

2017-10-11

Assessing the physical connections and allosteric communications in multi-domain nuclear receptor (NR) polypeptides has remained challenging, with few crystal structures available to show their overall structural organizations. Here we report the quaternary architecture of multi-domain retinoic acid receptor beta-retinoic X receptor alpha (RAR beta-RXR alpha) heterodimer bound to DNA, ligands and coactivator peptides, examined through crystallographic, hydrogen-deuterium exchange mass spectrometry, mutagenesis and functional studies. The RAR beta ligand-binding domain (LBD) and DNA-binding domain (DBD) are physically connected to foster allosteric signal transmission between them. Direct comparisons among all the multi-domain NRs studied crystallographically to date show significant variations within theirmore » quaternary architectures, rather than a common architecture adhering to strict rules. RXR remains flexible and adaptive by maintaining loosely organized domains, while its hetero-dimerization partners use a surface patch on their LBDs to form domain-domain interactions with DBDs.« less

The quaternary architecture of RARβ–RXRα heterodimer facilitates domain–domain signal transmission

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chandra, Vikas; Wu, Dalei; Li, Sheng

Assessing the physical connections and allosteric communications in multi-domain nuclear receptor (NR) polypeptides has remained challenging, with few crystal structures available to show their overall structural organizations. Here we report the quaternary architecture of multi-domain retinoic acid receptor beta-retinoic X receptor alpha (RAR beta-RXR alpha) heterodimer bound to DNA, ligands and coactivator peptides, examined through crystallographic, hydrogen-deuterium exchange mass spectrometry, mutagenesis and functional studies. The RAR beta ligand-binding domain (LBD) and DNA-binding domain (DBD) are physically connected to foster allosteric signal transmission between them. Direct comparisons among all the multi-domain NRs studied crystallographically to date show significant variations within theirmore » quaternary architectures, rather than a common architecture adhering to strict rules. RXR remains flexible and adaptive by maintaining loosely organized domains, while its hetero-dimerization partners use a surface patch on their LBDs to form domain-domain interactions with DBDs.« less

Beyond the "c" and the "x": Learning with algorithms in massive open online courses (MOOCs)

NASA Astrophysics Data System (ADS)

Knox, Jeremy

2018-02-01

This article examines how algorithms are shaping student learning in massive open online courses (MOOCs). Following the dramatic rise of MOOC platform organisations in 2012, over 4,500 MOOCs have been offered to date, in increasingly diverse languages, and with a growing requirement for fees. However, discussions of learning in MOOCs remain polarised around the "xMOOC" and "cMOOC" designations. In this narrative, the more recent extended or platform MOOC ("xMOOC") adopts a broadcast pedagogy, assuming a direct transmission of information to its largely passive audience (i.e. a teacher-centred approach), while the slightly older connectivist model ("cMOOC") offers only a simplistic reversal of the hierarchy, posing students as highly motivated, self-directed and collaborative learners (i.e. a learner-centred approach). The online nature of both models generates data (e.g. on how many times a particular resource was viewed, or the ways in which participants communicated with each other) which MOOC providers use for analysis, albeit only after these data have been selectively processed. Central to many learning analytics approaches is the desire to predict students' future behaviour. Educators need to be aware that MOOC learning is not just about teachers and students, but that it also involves algorithms: instructions which perform automated calculations on data. Education is becoming embroiled in an "algorithmic culture" that defines educational roles, forecasts attainment, and influences pedagogy. Established theories of learning appear wholly inadequate in addressing the agential role of algorithms in the educational domain of the MOOC. This article identifies and examines four key areas where algorithms influence the activities of the MOOC: (1) data capture and discrimination; (2) calculated learners; (3) feedback and entanglement; and (4) learning with algorithms. The article concludes with a call for further research in these areas to surface a critical discourse around the use of algorithms in MOOC education and beyond.

Optimizing Earth Data Search Ranking using Deep Learning and Real-time User Behaviour

NASA Astrophysics Data System (ADS)

Jiang, Y.; Yang, C. P.; Armstrong, E. M.; Huang, T.; Moroni, D. F.; McGibbney, L. J.; Greguska, F. R., III

2017-12-01

Finding Earth science data has been a challenging problem given both the quantity of data available and the heterogeneity of the data across a wide variety of domains. Current search engines in most geospatial data portals tend to induce end users to focus on one single data characteristic dimension (e.g., term frequency-inverse document frequency (TF-IDF) score, popularity, release date, etc.). This approach largely fails to take account of users' multidimensional preferences for geospatial data, and hence may likely result in a less than optimal user experience in discovering the most applicable dataset out of a vast range of available datasets. With users interacting with search engines, sufficient information is already hidden in the log files. Compared with explicit feedback data, information that can be derived/extracted from log files is virtually free and substantially more timely. In this dissertation, I propose an online deep learning framework that can quickly update the learning function based on real-time user clickstream data. The contributions of this framework include 1) a log processor that can ingest, process and create training data from web logs in a real-time manner; 2) a query understanding module to better interpret users' search intent using web log processing results and metadata; 3) a feature extractor that identifies ranking features representing users' multidimensional interests of geospatial data; and 4) a deep learning based ranking algorithm that can be trained incrementally using user behavior data. The search ranking results will be evaluated using precision at K and normalized discounted cumulative gain (NDCG).

Risk factors for dating violence versus cohabiting violence: Results from the third generation of the Cambridge Study in Delinquent Development.

PubMed

Theobald, Delphine; Farrington, David P; Ttofi, Maria M; Crago, Rebecca V

2016-10-01

Dating violence is an important problem. Evidence suggests that women are more likely to perpetrate dating violence. The present study investigates the prevalence of dating violence compared with cohabiting violence in a community sample of men and women and assesses to what extent child and adolescent explanatory factors predict this behaviour. A secondary aim is to construct a risk score for dating violence based on the strongest risk factors. The Cambridge Study in Delinquent Development is a prospective longitudinal survey of 411 men (generation 2) born in the 1950s in an inner London area. Most recently, their sons and daughters [generation 3 (G3)] have been interviewed regarding their perpetration of dating and cohabiting violence, utilising the Conflict Tactics Scale. Risk factors were measured in four domains (family, parental, socio-economic and individual). A larger proportion of women than men perpetrated at least one act of violence towards their dating partner (36.4 vs 21.7%). There was a similar pattern for cohabiting violence (39.6 vs 21.4%). A number of risk factors were significantly associated with the perpetration of dating violence. For G3 women, these included a convicted father, parental conflict, large family size and poor housing. For G3 men, these included having a young father or mother, separation from the father before age 16, early school leaving, frequent truancy and having a criminal conviction. A risk score for both men and women, based on 10 risk factors, significantly predicted dating violence. Risk factors from four domains were important in predicting dating violence, but they were different for G3 men and women. It may be important to consider different risk factors and different risk assessments for male compared with female perpetration of dating violence. Early identification and interventions are recommended. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Students' experiences of blended learning across a range of postgraduate programmes.

PubMed

Smyth, Siobhan; Houghton, Catherine; Cooney, Adeline; Casey, Dympna

2012-05-01

The article describes the students' experiences of taking a blended learning postgraduate programme in a school of nursing and midwifery. The indications to date are that blended learning as a pedagogical tool has the potential to contribute and improve nursing and midwifery practice and enhance student learning. Little is reported about the students' experiences to date. Focus groups were conducted with students in the first year of introducing blended learning. The two main themes that were identified from the data were (1) the benefits of blended learning and (2) the challenges to blended learning. The blended learning experience was received positively by the students. A significant finding that was not reported in previous research was that the online component meant little time away from study for the students suggesting that it was more invasive on their everyday life. It is envisaged that the outcomes of the study will assist educators who are considering delivering programmes through blended learning. It should provide guidance for further developments and improvements in using Virtual Learning Environment (VLE) and blended learning in nurse education. Copyright © 2011 Elsevier Ltd. All rights reserved.

Creativity in the Age of Technology: Measuring the Digital Creativity of Millennials

ERIC Educational Resources Information Center

Hoffmann, Jessica; Ivcevic, Zorana; Brackett, Marc

2016-01-01

Digital technology and its many uses form an emerging domain of creative expression for adolescents and young adults. To date, measures of self-reported creative behavior cover more traditional forms of creativity, including visual art, music, or writing, but do not include creativity in the digital domain. This article introduces a new measure,…

Technological Pedagogical Content Knowledge of Prospective Mathematics Teacher in Three Dimensional Material Based on Sex Differences

NASA Astrophysics Data System (ADS)

Aqib, M. A.; Budiarto, M. T.; Wijayanti, P.

2018-01-01

The effectiveness of learning in this era can be seen from 3 factors such as: technology, content, and pedagogy that covered in Technological Pedagogical Content Knowledge (TPCK). This research was a qualitative research which aimed to describe each domain from TPCK include Content Knowledge, Pedagogical Knowledge, Pedagogical Content Knowledge, Technological Knowledge, Technological Content Knowledge, Technological Pedagogical Knowledge and Technological, Pedagogical, and Content Knowledge. The subjects of this research were male and female mathematics college students at least 5th semester who has almost the same ability for some course like innovative learning, innovative learning II, school mathematics I, school mathematics II, computer applications and instructional media. Research began by spreading the questionnaire of subject then continued with the assignment and interview. The obtained data was validated by time triangulation.This research has result that male and female prospective teacher was relatively same for Content Knowledge and Pedagogical Knowledge domain. While it was difference in the Technological Knowledge domain. The difference in this domain certainly has an impact on other domains that has technology components on it. Although it can be minimized by familiarizing the technology.

A Pirate's Life: A Model and a Metaphor for Learning.

ERIC Educational Resources Information Center

Solomon, David L.

2002-01-01

Discusses various ways in which context may be interpreted to enhance learning and performance; illustrates domains of learning using a hockey team as an example; and suggests implications for learning, performance, and instructional design. Highlights include an ecological systems model; and examples of individual development, team learning, and…

An Examination of Learning Profiles in Physical Education

ERIC Educational Resources Information Center

Shen, Bo; Chen, Ang

2007-01-01

Using the model of domain learning as a theoretical framework, the study was designed to examine the extent to which learners' initial learning profiles based on previously acquired knowledge, learning strategy application, and interest-based motivation were distinctive in learning softball. Participants were 177 sixth-graders from three middle…

The Value of Significant Learning Strategies in Undergraduate Education

ERIC Educational Resources Information Center

Coco, Charles M.

2012-01-01

Learning taxonomies can assist faculty in developing course structures that promote enhanced student learning in the cognitive and affective domains. Significant Learning is one approach to course design that allows for development in six key areas: Foundational Knowledge, Application, Integration, Human Dimension, Caring, and Learning How to…

Procedural Learning and Individual Differences in Language

PubMed Central

Lee, Joanna C.; Tomblin, J. Bruce

2014-01-01

The aim of the current study was to examine different aspects of procedural memory in young adults who varied with regard to their language abilities. We selected a sample of procedural memory tasks, each of which represented a unique type of procedural learning, and has been linked, at least partially, to the functionality of the corticostriatal system. The findings showed that variance in language abilities is associated with performance on different domains of procedural memory, including the motor domain (as shown in the pursuit rotor task), the cognitive domain (as shown in the weather prediction task), and the linguistic domain (as shown in the nonword repetition priming task). These results implicate the corticostriatal system in individual differences in language. PMID:26190949

It's Greek to me: Domain specific relationships between intellectual helplessness and academic performance.

PubMed

Krejtz, Izabela; Nezlek, John B

2016-01-01

In a study of the domain specificity of intellectual learned helplessness, we collected data from 376 students in 14 classrooms. We measured feelings of intellectual helplessness for mathematics and language skills, anxiety about performance in each of these domains, and general working memory. Multilevel modeling analyses found that feelings of helplessness in language skills were negatively related to grades in language but were unrelated to grades in mathematics. Similarly, feelings of helplessness in mathematics were negatively related to grades in mathematics but were unrelated to grades in language. Controlling for anxiety or working memory did not change these relationships, nor did they vary across the age of students. The results support conceptualizations in which learned helplessness has a domain specific component.

Switching from Bloom to the Medicine Wheel: Creating Learning Outcomes That Support Indigenous Ways of Knowing in Post-Secondary Education

ERIC Educational Resources Information Center

LaFever, Marcella

2016-01-01

Based on a review of works by Indigenous educators, this paper suggests a four-domain framework for developing course outcome statements that will serve all students, with a focus on better supporting the educational empowerment of Indigenous students. The framework expands the three domains of learning, pioneered by Bloom to a four-domain…

Towards a Framework of Using Knowledge Tools for Teaching by Solving Problems in Technology-Enhanced Learning Environment

ERIC Educational Resources Information Center

Kostousov, Sergei; Kudryavtsev, Dmitry

2017-01-01

Problem solving is a critical competency for modern world and also an effective way of learning. Education should not only transfer domain-specific knowledge to students, but also prepare them to solve real-life problems--to apply knowledge from one or several domains within specific situation. Problem solving as teaching tool is known for a long…

Relations between the Development of Future Time Perspective in Three Life Domains, Investment in Learning, and Academic Achievement

ERIC Educational Resources Information Center

Peetsma, Thea; van der Veen, Ineke

2011-01-01

Relations between the development of future time perspectives in three life domains (i.e., school and professional career, social relations, and leisure time) and changes in students' investment in learning and academic achievement were examined in this study. Participants were 584 students in the first and 584 in the second year of the lower…

Understanding infants' and children's social learning about foods: previous research and new prospects.

PubMed

Shutts, Kristin; Kinzler, Katherine D; DeJesus, Jasmine M

2013-03-01

Developmental psychologists have devoted significant attention to investigating how children learn from others' actions, emotions, and testimony. Yet most of this research has examined children's socially guided learning about artifacts. The present article focuses on a domain that has received limited attention from those interested in the development of social cognition: food. We begin by reviewing the available literature on infants' and children's development in the food domain and identify situations in which children evidence both successes and failures in their interactions with foods. We focus specifically on the role that other people play in guiding what children eat and argue that understanding patterns of successes and failures in the food domain requires an appreciation of eating as a social phenomenon. We next propose a series of questions for future research and suggest that examining food selection as a social phenomenon can shed light on mechanisms underlying children's learning from others and provide ideas for promoting healthy social relationships and eating behaviors early in development.

Domain-Specific and Domain-General Learning Factors Are Expressed in Genetically Heterogeneous CD-1 Mice

ERIC Educational Resources Information Center

Kolata, Stefan; Light, Kenneth; Matzel, Louis D.

2008-01-01

It has been established that both domain-specific (e.g. spatial) as well as domain-general (general intelligence) factors influence human cognition. However, the separation of these processes has rarely been attempted in studies using laboratory animals. Previously, we have found that the performances of outbred mice across a wide range of…

Research Into the Role of Students’ Affective Domain While Learning Geology in Field Environments

NASA Astrophysics Data System (ADS)

Elkins, J.

2009-12-01

Existing research programs in field-based geocognition include assessment of cognitive, psychomotor, and affective domains. Assessment of the affective domain often involves the use of instruments and techniques uncommon to the geosciences. Research regarding the affective domain also commonly results in the collection and production of qualitative data that is difficult for geoscientists to analyze due to their lack of familiarity with these data sets. However, important information about students’ affective responses to learning in field environments can be obtained by using these methods. My research program focuses on data produced by students’ affective responses to field-based learning environments, primarily among students at the introductory level. For this research I developed a Likert-scale Novelty Space Survey, which presents student ‘novelty space’ (Orion and Hofstien, 1993) as a polygon; the larger the polygons, the more novelty students are experiencing. The axises for these polygons correspond to novelty domains involving geographic, social, cognitive, and psychological factors. In addition to the Novelty Space Survey, data which I have collected/generated includes focus group interviews on the role of recreational experiences in geology field programs. I have also collected data concerning the motivating factors that cause students to take photographs on field trips. The results of these studies give insight to the emotional responses students have to learning in the field and are important considerations for practitioners of teaching in these environments. Collaborative investigations among research programs that cross university departments and include multiple institutions is critical at this point in development of geocognition as a field due to unfamiliarity with cognitive science methodology by practitioners teaching geosciences and the dynamic nature of field work by cognitive scientists. However, combining the efforts of cognitive scientists and practitioners of geoscience teaching into research teams is a recommended strategy for understanding the role of the affective domain in student learning in field environments.

Deep transfer learning for automatic target classification: MWIR to LWIR

NASA Astrophysics Data System (ADS)

Ding, Zhengming; Nasrabadi, Nasser; Fu, Yun

2016-05-01

Publisher's Note: This paper, originally published on 5/12/2016, was replaced with a corrected/revised version on 5/18/2016. If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance. When dealing with sparse or no labeled data in the target domain, transfer learning shows its appealing performance by borrowing the supervised knowledge from external domains. Recently deep structure learning has been exploited in transfer learning due to its attractive power in extracting effective knowledge through multi-layer strategy, so that deep transfer learning is promising to address the cross-domain mismatch. In general, cross-domain disparity can be resulted from the difference between source and target distributions or different modalities, e.g., Midwave IR (MWIR) and Longwave IR (LWIR). In this paper, we propose a Weighted Deep Transfer Learning framework for automatic target classification through a task-driven fashion. Specifically, deep features and classifier parameters are obtained simultaneously for optimal classification performance. In this way, the proposed deep structures can extract more effective features with the guidance of the classifier performance; on the other hand, the classifier performance is further improved since it is optimized on more discriminative features. Furthermore, we build a weighted scheme to couple source and target output by assigning pseudo labels to target data, therefore we can transfer knowledge from source (i.e., MWIR) to target (i.e., LWIR). Experimental results on real databases demonstrate the superiority of the proposed algorithm by comparing with others.

Recurrent neural networks with specialized word embeddings for health-domain named-entity recognition.

PubMed

Jauregi Unanue, Iñigo; Zare Borzeshi, Ehsan; Piccardi, Massimo

2017-12-01

Previous state-of-the-art systems on Drug Name Recognition (DNR) and Clinical Concept Extraction (CCE) have focused on a combination of text "feature engineering" and conventional machine learning algorithms such as conditional random fields and support vector machines. However, developing good features is inherently heavily time-consuming. Conversely, more modern machine learning approaches such as recurrent neural networks (RNNs) have proved capable of automatically learning effective features from either random assignments or automated word "embeddings". (i) To create a highly accurate DNR and CCE system that avoids conventional, time-consuming feature engineering. (ii) To create richer, more specialized word embeddings by using health domain datasets such as MIMIC-III. (iii) To evaluate our systems over three contemporary datasets. Two deep learning methods, namely the Bidirectional LSTM and the Bidirectional LSTM-CRF, are evaluated. A CRF model is set as the baseline to compare the deep learning systems to a traditional machine learning approach. The same features are used for all the models. We have obtained the best results with the Bidirectional LSTM-CRF model, which has outperformed all previously proposed systems. The specialized embeddings have helped to cover unusual words in DrugBank and MedLine, but not in the i2b2/VA dataset. We present a state-of-the-art system for DNR and CCE. Automated word embeddings has allowed us to avoid costly feature engineering and achieve higher accuracy. Nevertheless, the embeddings need to be retrained over datasets that are adequate for the domain, in order to adequately cover the domain-specific vocabulary. Copyright © 2017 Elsevier Inc. All rights reserved.

Learn about Respiratory Syncytial Virus (RSV)

MedlinePlus

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The Planning Illusion: Does Active Planning of a Learning Route Support Learning as Well as Learners Think It Does?

ERIC Educational Resources Information Center

Bonestroo, Wilco J.; de Jong, Ton

2012-01-01

Is actively planning one's learning route through a learning domain beneficial for learning? Moreover, can learners accurately judge the extent to which planning has been beneficial for them? This study examined the effects of active planning on learning. Participants received a tool in which they created a learning route themselves before…

An Object Oriented Approach to Improve the Precision of Learning Object Retrieval in a Self Learning Environment

ERIC Educational Resources Information Center

Raghuveer, V. R.; Tripathy, B. K.

2012-01-01

With the advancements in the WWW and ICT, the e-learning domain has developed very fast. Even many educational institutions these days have shifted their focus towards the e-learning and mobile learning environments. However, from the quality of learning point of view, which is measured in terms of "active learning" taking place, the…

"Mastery Learning" Como Metodo Psicoeducativo para Ninos con Problemas Especificos de Aprendizaje. ("Mastery Learning" as a Psychoeducational Method for Children with Specific Learning Problems.)

ERIC Educational Resources Information Center

Coya, Liliam de Barbosa; Perez-Coffie, Jorge

1982-01-01

"Mastery Learning" was compared with the "conventional" method of teaching reading skills to Puerto Rican children with specific learning disabilities. The "Mastery Learning" group showed significant gains in the cognitive and affective domains. Results suggested Mastery Learning is a more effective method of teaching…

Becoming an Educable Lifelong Learning Subject: Adult Graduates' Transitions in Education and Working Life

ERIC Educational Resources Information Center

Siivonen, Päivi

2016-01-01

Continuous learning and updating one's competences and abilities have become requirements for staying "up-to-date" and "at the top of one's game". Lifelong learning policy has been persuasive in its emphasis on equal learning opportunities for all: everyone has endless possibilities and capabilities to learn according to…

Computer Assisted Language Learning. Routledge Studies in Computer Assisted Language Learning

ERIC Educational Resources Information Center

Pennington, Martha

2011-01-01

Computer-assisted language learning (CALL) is an approach to language teaching and learning in which computer technology is used as an aid to the presentation, reinforcement and assessment of material to be learned, usually including a substantial interactive element. This books provides an up-to date and comprehensive overview of…

How to Enhance Interdisciplinary Competence--Interdisciplinary Problem-Based Learning versus Interdisciplinary Project-Based Learning

ERIC Educational Resources Information Center

Brassler, Mirjam; Dettmers, Jan

2017-01-01

Interdisciplinary competence is important in academia for both employability and sustainable development. However, to date, there are no specific interdisciplinary education models and, naturally, no empirical studies to assess them. Since problem-based learning (PBL) and project-based learning (PjBL) are learning approaches that emphasize…

Multimodal Learning Analytics and Education Data Mining: Using Computational Technologies to Measure Complex Learning Tasks

ERIC Educational Resources Information Center

Blikstein, Paulo; Worsley, Marcelo

2016-01-01

New high-frequency multimodal data collection technologies and machine learning analysis techniques could offer new insights into learning, especially when students have the opportunity to generate unique, personalized artifacts, such as computer programs, robots, and solutions engineering challenges. To date most of the work on learning analytics…

Competency-based Radiology Residency: A Survey of Expectations from Singapore's Perspective.

PubMed

Yang, Hui; Tan, Colin J X; Lau, Doreen A H; Lim, Winston E H; Tay, Kiang Hiong; Kei, Pin Lin

2015-03-01

In response to the demands of an ageing nation, the postgraduate medical education in Singapore is currently in the early stage of transition into the American-styled residency programme. This study assessed the expectations of both radiology trainees and faculty on their ideal clinical learning environment (CLE) which facilitates the programme development. A modified 23-item questionnaire was administered to both trainees and faculty at a local training hospital. All items were scored according to their envisioned level of importance and categorised into 5 main CLE domains-supervision, formal training programme, work-based learning, social atmosphere and workload. 'Supervision' was identified as the most important domain of the CLE by both trainees and faculty, followed by 'formal training programmes', 'work-based learning' and 'social atmosphere'. 'Workload' was rated as the least important domain. For all domains, the reported expectation between both trainees and faculty respondents did not differ significantly. Intragroup comparison also showed no significant difference within each group of respondents. This study has provided valuable insights on both respondents' expectations on their ideal CLE that can best train competency in future radiologists. Various approaches to address these concerns were also discussed. The similarities in findings between ours and previous studies suggest that the 'supervision', 'formal training programmes' and 'work-based learning' domains are crucial for the success of a postgraduate medical training and should be emphasised in future curriculum. 'Workload' remains a challenge in postgraduate medical training, but attempts to address this will have an impact in future radiology training.

Pairwise domain adaptation module for CNN-based 2-D/3-D registration.

PubMed

Zheng, Jiannan; Miao, Shun; Jane Wang, Z; Liao, Rui

2018-04-01

Accurate two-dimensional to three-dimensional (2-D/3-D) registration of preoperative 3-D data and intraoperative 2-D x-ray images is a key enabler for image-guided therapy. Recent advances in 2-D/3-D registration formulate the problem as a learning-based approach and exploit the modeling power of convolutional neural networks (CNN) to significantly improve the accuracy and efficiency of 2-D/3-D registration. However, for surgery-related applications, collecting a large clinical dataset with accurate annotations for training can be very challenging or impractical. Therefore, deep learning-based 2-D/3-D registration methods are often trained with synthetically generated data, and a performance gap is often observed when testing the trained model on clinical data. We propose a pairwise domain adaptation (PDA) module to adapt the model trained on source domain (i.e., synthetic data) to target domain (i.e., clinical data) by learning domain invariant features with only a few paired real and synthetic data. The PDA module is designed to be flexible for different deep learning-based 2-D/3-D registration frameworks, and it can be plugged into any pretrained CNN model such as a simple Batch-Norm layer. The proposed PDA module has been quantitatively evaluated on two clinical applications using different frameworks of deep networks, demonstrating its significant advantages of generalizability and flexibility for 2-D/3-D medical image registration when a small number of paired real-synthetic data can be obtained.

The Semantic Learning Organization

ERIC Educational Resources Information Center

Sicilia, Miguel-Angel; Lytras, Miltiadis D.

2005-01-01

Purpose: The aim of this paper is introducing the concept of a "semantic learning organization" (SLO) as an extension of the concept of "learning organization" in the technological domain. Design/methodology/approach: The paper takes existing definitions and conceptualizations of both learning organizations and Semantic Web technology to develop…

Large-scale Labeled Datasets to Fuel Earth Science Deep Learning Applications

NASA Astrophysics Data System (ADS)

Maskey, M.; Ramachandran, R.; Miller, J.

2017-12-01

Deep learning has revolutionized computer vision and natural language processing with various algorithms scaled using high-performance computing. However, generic large-scale labeled datasets such as the ImageNet are the fuel that drives the impressive accuracy of deep learning results. Large-scale labeled datasets already exist in domains such as medical science, but creating them in the Earth science domain is a challenge. While there are ways to apply deep learning using limited labeled datasets, there is a need in the Earth sciences for creating large-scale labeled datasets for benchmarking and scaling deep learning applications. At the NASA Marshall Space Flight Center, we are using deep learning for a variety of Earth science applications where we have encountered the need for large-scale labeled datasets. We will discuss our approaches for creating such datasets and why these datasets are just as valuable as deep learning algorithms. We will also describe successful usage of these large-scale labeled datasets with our deep learning based applications.

Development and implementation of a balanced scorecard in an academic hospitalist group.

PubMed

Hwa, Michael; Sharpe, Bradley A; Wachter, Robert M

2013-03-01

Academic hospitalist groups (AHGs) are often expected to excel in multiple domains: quality improvement, patient safety, education, research, administration, and clinical care. To be successful, AHGs must develop strategies to balance their energies, resources, and performance. The balanced scorecard (BSC) is a strategic management system that enables organizations to translate their mission and vision into specific objectives and metrics across multiple domains. To date, no hospitalist group has reported on BSC implementation. We set out to develop a BSC as part of a strategic planning initiative. Based on a needs assessment of the University of California, San Francisco, Division of Hospital Medicine, mission and vision statements were developed. We engaged representative faculty to develop strategic objectives and determine performance metrics across 4 BSC perspectives. There were 41 metrics identified, and 16 were chosen for the initial BSC. It allowed us to achieve several goals: 1) present a broad view of performance, 2) create transparency and accountability, 3) communicate goals and engage faculty, and 4) ensure we use data to guide strategic decisions. Several lessons were learned, including the need to build faculty consensus, establish metrics with reliable measureable data, and the power of the BSC to drive goals across the division. We successfully developed and implemented a BSC in an AHG as part of a strategic planning initiative. The BSC has been instrumental in allowing us to achieve balanced success in multiple domains. Academic groups should consider employing the BSC as it allows for a data-driven strategic planning and assessment process. Copyright © 2013 Society of Hospital Medicine.

Separate functional properties of NMDARs regulate distinct aspects of spatial cognition.

PubMed

Sanders, Erin M; Nyarko-Odoom, Akua O; Zhao, Kevin; Nguyen, Michael; Liao, Hong Hong; Keith, Matthew; Pyon, Jane; Kozma, Alyssa; Sanyal, Mohima; McHail, Daniel G; Dumas, Theodore C

2018-06-01

N -methyl-d-aspartate receptors (NMDARs) at excitatory synapses are central to activity-dependent synaptic plasticity and learning and memory. NMDARs act as ionotropic and metabotropic receptors by elevating postsynaptic calcium concentrations and by direct intracellular protein signaling. In the forebrain, these properties are controlled largely by the auxiliary GluN2 subunits, GluN2A and GluN2B. While calcium conductance through NMDAR channels and intracellular protein signaling make separate contributions to synaptic plasticity, it is not known if these properties individually influence learning and memory. To address this issue, we created chimeric GluN2 subunits containing the amino-terminal domain and transmembrane domains from GluN2A or GluN2B fused to the carboxy-terminal domain of GluN2B (termed ABc) or GluN2A ATD (termed BAc), respectively, and expressed these mutated GluN2 subunits in transgenic mice. Expression was confirmed at the mRNA level and protein subunit translation and translocation into dendrites were observed in forebrain neurons. In the spatial version of the Morris water maze, BAc mice displayed signs of a learning deficit. In contrast, ABc animals performed similarly to wild-types during training, but showed a more direct approach to the goal location during a long-term memory test. There was no effect of ABc or BAc expression in a nonspatial water escape task. Since background expression is predominantly GluN2A in mature animals, the results suggest that spatial learning is more sensitive to manipulations of the amino-terminal domain and transmembrane domains (calcium conductance) and long-term memory is regulated more by the carboxy-terminal domain (intracellular protein signaling). © 2018 Sanders et al.; Published by Cold Spring Harbor Laboratory Press.

Dashboard for Analyzing Ubiquitous Learning Log

ERIC Educational Resources Information Center

Lkhagvasuren, Erdenesaikhan; Matsuura, Kenji; Mouri, Kousuke; Ogata, Hiroaki

2016-01-01

Mobile and ubiquitous technologies have been applied to a wide range of learning fields such as science, social science, history and language learning. Many researchers have been investigating the development of ubiquitous learning environments; nevertheless, to date, there have not been enough research works related to the reflection, analysis…

Rapid Training of Information Extraction with Local and Global Data Views

DTIC Science & Technology

2012-05-01

56 xiii 4.1 An example of words and their bit string representations. Bold ones are transliterated Arabic words...Natural Language Processing ( NLP ) community faces new tasks and new domains all the time. Without enough labeled data of a new task or a new domain to...conduct supervised learning, semi-supervised learning is particularly attractive to NLP researchers since it only requires a handful of labeled examples

A Multi-Agent Question-Answering System for E-Learning and Collaborative Learning Environment

ERIC Educational Resources Information Center

Alinaghi, Tannaz; Bahreininejad, Ardeshir

2011-01-01

The increasing advances of new Internet technologies in all application domains have changed life styles and interactions. E-learning and collaborative learning environment systems are originated through such changes and aim at providing facilities for people in different times and geographical locations to cooperate, collaborate, learn and work…

Workplace, Organizational, and Societal: Three Domains of Learning for 21st-Century Cities

ERIC Educational Resources Information Center

Yorks, Lyle; Barto, Jody

2015-01-01

Interconnections between workplace and organizational learning can highlight the ongoing changes taking place that prestage the need for learning cities and regions. The diverse institutions that comprise cities and regions can function as organizational learning mechanisms in the 21st century. Learning cities themselves can also be conceptualized…

Mobile Learning as Boundary Crossing: An Alternative Route to Technology-Enhanced Learning?

ERIC Educational Resources Information Center

Pimmer, Christoph

2016-01-01

This paper examines digital and mobile learning that goes beyond bounded communities and closed domains. While recent work from the field of mobile learning has emphasized the importance of learning across "contexts," little analytical attention has been paid to the underlying dynamics of this phenomenon. To illuminate this, the four…

Sulphate incorporation in monazite lattice and dating the cycle of sulphur in metamorphic belts

NASA Astrophysics Data System (ADS)

Laurent, Antonin T.; Seydoux-Guillaume, Anne-Magali; Duchene, Stéphanie; Bingen, Bernard; Bosse, Valérie; Datas, Lucien

2016-11-01

Microgeochemical data and transmission electron microscope (TEM) imaging of S-rich monazite crystals demonstrate that S has been incorporated in the lattice of monazite as a clino-anhydrite component via the following exchange Ca2+ + S6+ = REE3+ + P5+, and that it is now partly exsolved in nanoclusters (5-10 nm) of CaSO4. The sample, an osumilite-bearing ultra-high-temperature granulite from Rogaland, Norway, is characterized by complexly patchy zoned monazite crystals. Three chemical domains are distinguished as (1) a sulphate-rich core (0.45-0.72 wt% SO2, Th incorporated as cheralite component), (2) secondary sulphate-bearing domains (SO2 >0.05 wt%, partly clouded with solid inclusions), and (3) late S-free, Y-rich domains (0.8-2.5 wt% Y2O3, Th accommodated as the huttonite component). These three domains yield distinct isotopic U-Pb ages of 1034 ± 6, 1005 ± 7, and 935 ± 7 Ma, respectively. Uranium-Th-Pb EPMA dating independently confirms these ages. This study illustrates that it is possible to discriminate different generations of monazite based on their S contents. From the petrological context, we propose that sulphate-rich monazite reflects high-temperature Fe-sulphide breakdown under oxidizing conditions, coeval with biotite dehydration melting. Monazite may therefore reveal the presence of S in anatectic melts from high-grade terrains at a specific point in time and date S mobilization from a reduced to an oxidized state. This property can be used to investigate the mineralization potential of a given geological event within a larger orogenic framework.

Not-so-social learning strategies.

PubMed

Heyes, Cecilia; Pearce, John M

2015-03-07

Social learning strategies (SLSs) are rules specifying the conditions in which it would be adaptive for animals to copy the behaviour of others rather than to persist with a previously established behaviour or to acquire a new behaviour through asocial learning. In behavioural ecology, cultural evolutionary theory and economics, SLSs are studied using a 'phenotypic gambit'-from a purely functional perspective, without reference to their underlying psychological mechanisms. However, SLSs are described in these fields as if they were implemented by complex, domain-specific, genetically inherited mechanisms of decision-making. In this article, we suggest that it is time to begin investigating the psychology of SLSs, and we initiate this process by examining recent experimental work relating to three groups of strategies: copy when alternative unsuccessful, copy when model successful and copy the majority. In each case, we argue that the reported behaviour could have been mediated by domain-general and taxonomically general psychological mechanisms; specifically, by mechanisms, identified through conditioning experiments, that make associative learning selective. We also suggest experimental manipulations that could be used in future research to resolve more fully the question whether, in non-human animals, SLSs are mediated by domain-general or domain-specific psychological mechanisms. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Quality specifications in postgraduate medical e-learning: an integrative literature review leading to a postgraduate medical e-learning model.

PubMed

De Leeuw, R A; Westerman, Michiel; Nelson, E; Ket, J C F; Scheele, F

2016-07-08

E-learning is driving major shifts in medical education. Prioritizing learning theories and quality models improves the success of e-learning programs. Although many e-learning quality standards are available, few are focused on postgraduate medical education. We conducted an integrative review of the current postgraduate medical e-learning literature to identify quality specifications. The literature was thematically organized into a working model. Unique quality specifications (n = 72) were consolidated and re-organized into a six-domain model that we called the Postgraduate Medical E-learning Model (Postgraduate ME Model). This model was partially based on the ISO-19796 standard, and drew on cognitive load multimedia principles. The domains of the model are preparation, software design and system specifications, communication, content, assessment, and maintenance. This review clarified the current state of postgraduate medical e-learning standards and specifications. It also synthesized these specifications into a single working model. To validate our findings, the next-steps include testing the Postgraduate ME Model in controlled e-learning settings.

Resident Space Object Characterization and Behavior Understanding via Machine Learning and Ontology-based Bayesian Networks

NASA Astrophysics Data System (ADS)

Furfaro, R.; Linares, R.; Gaylor, D.; Jah, M.; Walls, R.

2016-09-01

In this paper, we present an end-to-end approach that employs machine learning techniques and Ontology-based Bayesian Networks (BN) to characterize the behavior of resident space objects. State-of-the-Art machine learning architectures (e.g. Extreme Learning Machines, Convolutional Deep Networks) are trained on physical models to learn the Resident Space Object (RSO) features in the vectorized energy and momentum states and parameters. The mapping from measurements to vectorized energy and momentum states and parameters enables behavior characterization via clustering in the features space and subsequent RSO classification. Additionally, Space Object Behavioral Ontologies (SOBO) are employed to define and capture the domain knowledge-base (KB) and BNs are constructed from the SOBO in a semi-automatic fashion to execute probabilistic reasoning over conclusions drawn from trained classifiers and/or directly from processed data. Such an approach enables integrating machine learning classifiers and probabilistic reasoning to support higher-level decision making for space domain awareness applications. The innovation here is to use these methods (which have enjoyed great success in other domains) in synergy so that it enables a "from data to discovery" paradigm by facilitating the linkage and fusion of large and disparate sources of information via a Big Data Science and Analytics framework.

Domain learning naming game for color categorization.

PubMed

Li, Doujie; Fan, Zhongyan; Tang, Wallace K S

2017-01-01

Naming game simulates the evolution of vocabulary in a population of agents. Through pairwise interactions in the games, agents acquire a set of vocabulary in their memory for object naming. The existing model confines to a one-to-one mapping between a name and an object. Focus is usually put onto name consensus in the population rather than knowledge learning in agents, and hence simple learning model is usually adopted. However, the cognition system of human being is much more complex and knowledge is usually presented in a complicated form. Therefore, in this work, we extend the agent learning model and design a new game to incorporate domain learning, which is essential for more complicated form of knowledge. In particular, we demonstrate the evolution of color categorization and naming in a population of agents. We incorporate the human perceptive model into the agents and introduce two new concepts, namely subjective perception and subliminal stimulation, in domain learning. Simulation results show that, even without any supervision or pre-requisition, a consensus of a color naming system can be reached in a population solely via the interactions. Our work confirms the importance of society interactions in color categorization, which is a long debate topic in human cognition. Moreover, our work also demonstrates the possibility of cognitive system development in autonomous intelligent agents.

Domain learning naming game for color categorization

PubMed Central

2017-01-01

Naming game simulates the evolution of vocabulary in a population of agents. Through pairwise interactions in the games, agents acquire a set of vocabulary in their memory for object naming. The existing model confines to a one-to-one mapping between a name and an object. Focus is usually put onto name consensus in the population rather than knowledge learning in agents, and hence simple learning model is usually adopted. However, the cognition system of human being is much more complex and knowledge is usually presented in a complicated form. Therefore, in this work, we extend the agent learning model and design a new game to incorporate domain learning, which is essential for more complicated form of knowledge. In particular, we demonstrate the evolution of color categorization and naming in a population of agents. We incorporate the human perceptive model into the agents and introduce two new concepts, namely subjective perception and subliminal stimulation, in domain learning. Simulation results show that, even without any supervision or pre-requisition, a consensus of a color naming system can be reached in a population solely via the interactions. Our work confirms the importance of society interactions in color categorization, which is a long debate topic in human cognition. Moreover, our work also demonstrates the possibility of cognitive system development in autonomous intelligent agents. PMID:29136661

Deep learning for healthcare: review, opportunities and challenges.

PubMed

Miotto, Riccardo; Wang, Fei; Wang, Shuang; Jiang, Xiaoqian; Dudley, Joel T

2017-05-06

Gaining knowledge and actionable insights from complex, high-dimensional and heterogeneous biomedical data remains a key challenge in transforming health care. Various types of data have been emerging in modern biomedical research, including electronic health records, imaging, -omics, sensor data and text, which are complex, heterogeneous, poorly annotated and generally unstructured. Traditional data mining and statistical learning approaches typically need to first perform feature engineering to obtain effective and more robust features from those data, and then build prediction or clustering models on top of them. There are lots of challenges on both steps in a scenario of complicated data and lacking of sufficient domain knowledge. The latest advances in deep learning technologies provide new effective paradigms to obtain end-to-end learning models from complex data. In this article, we review the recent literature on applying deep learning technologies to advance the health care domain. Based on the analyzed work, we suggest that deep learning approaches could be the vehicle for translating big biomedical data into improved human health. However, we also note limitations and needs for improved methods development and applications, especially in terms of ease-of-understanding for domain experts and citizen scientists. We discuss such challenges and suggest developing holistic and meaningful interpretable architectures to bridge deep learning models and human interpretability. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Supporting Semantic Annotation of Educational Content by Automatic Extraction of Hierarchical Domain Relationships

ERIC Educational Resources Information Center

Vrablecová, Petra; Šimko, Marián

2016-01-01

The domain model is an essential part of an adaptive learning system. For each educational course, it involves educational content and semantics, which is also viewed as a form of conceptual metadata about educational content. Due to the size of a domain model, manual domain model creation is a challenging and demanding task for teachers or…

Domain-Specificity of Self-Concept and Parent Expectation Influences on Short-Term and Long-Term Learning of Physics

ERIC Educational Resources Information Center

Yeung, Alexander Seeshing; Kuppan, Loganantham; Foong, See Kit; Wong, Darren Jon Sien; Kadir, Munirah Shaik; Lee, Paul Choon Keat; Yau, Che Ming

2010-01-01

Background: Students' academic self-concepts are known to be domain specific. Researchers have also identified two related components of self-concept:cognitive (how competent students feel about a subject domain) and affective (their interest in the subject). This paper examines whether both components are domain specific. Research has also shown…

29 CFR 29.8 - Deregistration of a registered program.

Code of Federal Regulations, 2012 CFR

2012-07-01

... at the sponsor's request, and the effective date thereof; (2) That, within 15 days of the date of the acknowledgment, the sponsor will notify all apprentices of such cancellation and the effective date; that such... learning; failure to provide related instruction; failure to pay the apprentice a progressively increasing...

38 CFR 21.4258 - Notice of approval.

Code of Federal Regulations, 2012 CFR

2012-07-01

... include the following: (1) For an educational institution: (i) Date of the letter and effective date of... course approved at an institution of higher learning, may identify approved courses by reference to page... appropriate State approving agency. (2) For a training establishment: (i) Date of the letter and effective...

29 CFR 29.8 - Deregistration of a registered program.

Code of Federal Regulations, 2014 CFR

2014-07-01

... at the sponsor's request, and the effective date thereof; (2) That, within 15 days of the date of the acknowledgment, the sponsor will notify all apprentices of such cancellation and the effective date; that such... learning; failure to provide related instruction; failure to pay the apprentice a progressively increasing...

38 CFR 21.4258 - Notice of approval.

Code of Federal Regulations, 2014 CFR

2014-07-01

... include the following: (1) For an educational institution: (i) Date of the letter and effective date of... course approved at an institution of higher learning, may identify approved courses by reference to page... appropriate State approving agency. (2) For a training establishment: (i) Date of the letter and effective...

29 CFR 29.8 - Deregistration of a registered program.

Code of Federal Regulations, 2011 CFR

2011-07-01

... at the sponsor's request, and the effective date thereof; (2) That, within 15 days of the date of the acknowledgment, the sponsor will notify all apprentices of such cancellation and the effective date; that such... learning; failure to provide related instruction; failure to pay the apprentice a progressively increasing...

29 CFR 29.8 - Deregistration of a registered program.

Code of Federal Regulations, 2013 CFR

2013-07-01

... at the sponsor's request, and the effective date thereof; (2) That, within 15 days of the date of the acknowledgment, the sponsor will notify all apprentices of such cancellation and the effective date; that such... learning; failure to provide related instruction; failure to pay the apprentice a progressively increasing...

38 CFR 21.4258 - Notice of approval.

Code of Federal Regulations, 2013 CFR

2013-07-01

... include the following: (1) For an educational institution: (i) Date of the letter and effective date of... course approved at an institution of higher learning, may identify approved courses by reference to page... appropriate State approving agency. (2) For a training establishment: (i) Date of the letter and effective...

Developing Deep Learning Applications for Life Science and Pharma Industry.

PubMed

Siegismund, Daniel; Tolkachev, Vasily; Heyse, Stephan; Sick, Beate; Duerr, Oliver; Steigele, Stephan

2018-06-01

Deep Learning has boosted artificial intelligence over the past 5 years and is seen now as one of the major technological innovation areas, predicted to replace lots of repetitive, but complex tasks of human labor within the next decade. It is also expected to be 'game changing' for research activities in pharma and life sciences, where large sets of similar yet complex data samples are systematically analyzed. Deep learning is currently conquering formerly expert domains especially in areas requiring perception, previously not amenable to standard machine learning. A typical example is the automated analysis of images which are typically produced en-masse in many domains, e. g., in high-content screening or digital pathology. Deep learning enables to create competitive applications in so-far defined core domains of 'human intelligence'. Applications of artificial intelligence have been enabled in recent years by (i) the massive availability of data samples, collected in pharma driven drug programs (='big data') as well as (ii) deep learning algorithmic advancements and (iii) increase in compute power. Such applications are based on software frameworks with specific strengths and weaknesses. Here, we introduce typical applications and underlying frameworks for deep learning with a set of practical criteria for developing production ready solutions in life science and pharma research. Based on our own experience in successfully developing deep learning applications we provide suggestions and a baseline for selecting the most suited frameworks for a future-proof and cost-effective development. © Georg Thieme Verlag KG Stuttgart · New York.

Usability study of the EduMod eLearning Program for contouring nodal stations of the head and neck.

PubMed

Deraniyagala, Rohan; Amdur, Robert J; Boyer, Arthur L; Kaylor, Scott

2015-01-01

A major strategy for improving radiation oncology education and competence evaluation is to develop eLearning programs that reproduce the real work environment. A valuable measure of the quality of an eLearning program is "usability," which is a multidimensional endpoint defined from the end user's perspective. The gold standard for measuring usability is the Software Usability Measurement Inventory (SUMI). The purpose of this study is to use the SUMI to measure usability of an eLearning course that uses innovative software to teach and test contouring of nodal stations of the head and neck. This is a prospective institutional review board-approved study in which all participants gave written informed consent. The study population was radiation oncology residents from 8 different programs across the United States. The subjects had to pass all sections of the same 2 eLearning modules and then complete the SUMI usability evaluation instrument. We reached the accrual goal of 25 participants. Usability results for the EduMod eLearning course, "Nodal Stations of the Head and Neck," were compared with a large database of scores of other major software programs. Results were evaluated in 5 domains: Affect, Helpfulness, Control, Learnability, and Global Usability. In all 5 domains, usability scores for the study modules were higher than the database mean and statistically superior in 4 domains. This is the first study to evaluate usability of an eLearning program related to radiation oncology. Usability of 2 representative modules related to contouring nodal stations of the head and neck was highly favorable, with scores that were superior to the industry standard in multiple domains. These results support the continued development of this type of eLearning program for teaching and testing radiation oncology technical skills. Copyright © 2015 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.

Learning Potential and Cognitive Modifiability

ERIC Educational Resources Information Center

Kozulin, Alex

2011-01-01

The relationship between thinking and learning constitutes one of the fundamental problems of cognitive psychology. Though there is an obvious overlap between the domains of thinking and learning, it seems more productive to consider learning as being predominantly acquisition while considering thinking as the application of the existent concepts…

Implicit Statistical Learning and Language Skills in Bilingual Children

ERIC Educational Resources Information Center

Yim, Dongsun; Rudoy, John

2013-01-01

Purpose: Implicit statistical learning in 2 nonlinguistic domains (visual and auditory) was used to investigate (a) whether linguistic experience influences the underlying learning mechanism and (b) whether there are modality constraints in predicting implicit statistical learning with age and language skills. Method: Implicit statistical learning…

Challenges in Modeling and Measuring Learning Trajectories

ERIC Educational Resources Information Center

Confrey, Jere; Jones, R. Seth; Gianopulos, Garron

2015-01-01

Briggs and Peck make a compelling case for creating new, more intuitive measures of learning, based on creating vertical scales using learning trajectories (LT) in place of "domain sampling." We believe that the importance of creating measurement scales that coordinate recognizable landmarks in learning trajectories with interval scales…

Evaluation of a Chronic Disease Management System for the Treatment and Management of Diabetes in Primary Health Care Practices in Ontario

PubMed Central

DJ, O’Reilly; JM, Bowen; RJ, Sebaldt; A, Petrie; RB, Hopkins; N, Assasi; C, MacDougald; E, Nunes; R, Goeree

2014-01-01

Background Computerized chronic disease management systems (CDMSs), when aligned with clinical practice guidelines, have the potential to effectively impact diabetes care. Objective The objective was to measure the difference between optimal diabetes care and actual diabetes care before and after the introduction of a computerized CDMS. Methods This 1-year, prospective, observational, pre/post study evaluated the use of a CDMS with a diabetes patient registry and tracker in family practices using patient enrolment models. Aggregate practice-level data from all rostered diabetes patients were analyzed. The primary outcome measure was the change in proportion of patients with up-to-date “ABC” monitoring frequency (i.e., hemoglobin A1c, blood pressure, and cholesterol). Changes in the frequency of other practice care and treatment elements (e.g., retinopathy screening) were also determined. Usability and satisfaction with the CDMS were measured. Results Nine sites, 38 health care providers, and 2,320 diabetes patients were included. The proportion of patients with up-to-date ABC (12%), hemoglobin A1c (45%), and cholesterol (38%) monitoring did not change over the duration of the study. The proportion of patients with up-to-date blood pressure monitoring improved, from 16% to 20%. Data on foot examinations, retinopathy screening, use of angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers, and documentation of self-management goals were not available or not up to date at baseline for 98% of patients. By the end of the study, attitudes of health care providers were more negative on the Training, Usefulness, Daily Practice, and Support from the Service Provider domains of the CDMS, but more positive on the Learning, Using, Practice Planning, CDMS, and Satisfaction domains. Limitations Few practitioners used the CDMS, so it was difficult to draw conclusions about its efficacy. Simply giving health care providers a potentially useful technology will not ensure its use. Conclusions This real-world evaluation of a web-based CDMS for diabetes failed to impact physician practice due to limited use of the system. Plain Language Summary Patients and health care providers need timely access to information to ensure proper diabetes care. This study looked at whether a computer-based system at the doctor’s office could improve diabetes management. However, few clinics and health care providers used the system, so no improvement in diabetes care was seen. PMID:24748911

Student evaluation of clickers in a dental pathology course.

PubMed

Llena, Carmen; Forner, Leopoldo; Cueva, Roger

2015-07-01

The purpose of this study was to evaluate the degree of satisfaction of students and teachers, and to determine whether the students notice improvements in learning and in the learning environment as a result of the use of clicker. Descriptive study. Fifty-one students and 8 teachers participated in the use of clicker technology in 8 preclinical seminars in dental pathology. Students and teachers filled a three-domain questionnaire at the end of the preclinical course. We used the Mann-Whitney U-test to compare the results between the two groups. The domain "perception and expectation" showed the use of clickers to be simple and convenient for 80% of the students, who expressed interest in extending the practice to other teaching areas. In the domain "active learning", over 70% of the students found the technique to be dynamic, participative and motivating. In the domain "improved learning", over 70% considered it useful to know their level of knowledge before the seminar and found the contents of the lesson to be clear. Thirty percent considered the items of the examination to be of a complexity similar to that of the first and second tests. Only in this latter aspect were significant differences found between the teachers and students (p=0.001). Participants described the use of clickers as simple and useful, motivating and participative. Both the students and teachers considered the technique to improve teaching and the learning environment. Key words:Dental education, audience response system, clickers, classroom response system, student´s perception.

Deep Correlated Holistic Metric Learning for Sketch-Based 3D Shape Retrieval.

PubMed

Dai, Guoxian; Xie, Jin; Fang, Yi

2018-07-01

How to effectively retrieve desired 3D models with simple queries is a long-standing problem in computer vision community. The model-based approach is quite straightforward but nontrivial, since people could not always have the desired 3D query model available by side. Recently, large amounts of wide-screen electronic devices are prevail in our daily lives, which makes the sketch-based 3D shape retrieval a promising candidate due to its simpleness and efficiency. The main challenge of sketch-based approach is the huge modality gap between sketch and 3D shape. In this paper, we proposed a novel deep correlated holistic metric learning (DCHML) method to mitigate the discrepancy between sketch and 3D shape domains. The proposed DCHML trains two distinct deep neural networks (one for each domain) jointly, which learns two deep nonlinear transformations to map features from both domains into a new feature space. The proposed loss, including discriminative loss and correlation loss, aims to increase the discrimination of features within each domain as well as the correlation between different domains. In the new feature space, the discriminative loss minimizes the intra-class distance of the deep transformed features and maximizes the inter-class distance of the deep transformed features to a large margin within each domain, while the correlation loss focused on mitigating the distribution discrepancy across different domains. Different from existing deep metric learning methods only with loss at the output layer, our proposed DCHML is trained with loss at both hidden layer and output layer to further improve the performance by encouraging features in the hidden layer also with desired properties. Our proposed method is evaluated on three benchmarks, including 3D Shape Retrieval Contest 2013, 2014, and 2016 benchmarks, and the experimental results demonstrate the superiority of our proposed method over the state-of-the-art methods.

The Effects of Student Engagement, Student Satisfaction, and Perceived Learning in Online Learning Environments

ERIC Educational Resources Information Center

Gray, Julie A.; DiLoreto, Melanie

2016-01-01

Studies have shown that course organization and structure, student engagement, learner interaction, and instructor presence have accounted for considerable variance in student satisfaction and perceived learning in online learning environments through a range of pathways, although no research to date has tested the mediational relationship…

The Usefulness of Learning Objects in Industry Oriented Learning Environments

ERIC Educational Resources Information Center

Fernando, Shantha; Sol, Henk; Dahanayake, Ajantha

2012-01-01

A model is presented to evaluate the usefulness of learning objects for industry oriented learning environments that emphasise training university graduates for job opportunities in a competitive industry oriented economy. Knowledge workers of the industry seek continuous professional development to keep their skills and knowledge up to date. Many…

Preparing Teachers for Emerging Blended Learning Environments

ERIC Educational Resources Information Center

Oliver, Kevin M.; Stallings, Dallas T.

2014-01-01

Blended learning environments that merge learning strategies, resources, and modes have been implemented in higher education settings for nearly two decades, and research has identified many positive effects. More recently, K-12 traditional and charter schools have begun to experiment with blended learning, but to date, research on the effects of…

Lessons learned: A comparative study of the integration experiences of Armenian and Palestinian refugees in Lebanon

DTIC Science & Technology

2017-06-01

design is based on two comparative case studies, examining Palestinian and Armenian refugees in Lebanon, respectively. These two cases are particularly...A COMPARATIVE STUDY OF THE INTEGRATION EXPERIENCES OF ARMENIAN AND PALESTINIAN REFUGEES IN LEBANON by Pascal Ghobeira June 2017 Thesis...REPORT DATE June 2017 3. REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE LESSONS LEARNED: A COMPARATIVE STUDY OF THE

A Bayesian generative model for learning semantic hierarchies

PubMed Central

Mittelman, Roni; Sun, Min; Kuipers, Benjamin; Savarese, Silvio

2014-01-01

Building fine-grained visual recognition systems that are capable of recognizing tens of thousands of categories, has received much attention in recent years. The well known semantic hierarchical structure of categories and concepts, has been shown to provide a key prior which allows for optimal predictions. The hierarchical organization of various domains and concepts has been subject to extensive research, and led to the development of the WordNet domains hierarchy (Fellbaum, 1998), which was also used to organize the images in the ImageNet (Deng et al., 2009) dataset, in which the category count approaches the human capacity. Still, for the human visual system, the form of the hierarchy must be discovered with minimal use of supervision or innate knowledge. In this work, we propose a new Bayesian generative model for learning such domain hierarchies, based on semantic input. Our model is motivated by the super-subordinate organization of domain labels and concepts that characterizes WordNet, and accounts for several important challenges: maintaining context information when progressing deeper into the hierarchy, learning a coherent semantic concept for each node, and modeling uncertainty in the perception process. PMID:24904452

Ontology Extraction Tools: An Empirical Study with Educators

ERIC Educational Resources Information Center

Hatala, M.; Gasevic, D.; Siadaty, M.; Jovanovic, J.; Torniai, C.

2012-01-01

Recent research in Technology-Enhanced Learning (TEL) demonstrated several important benefits that semantic technologies can bring to the TEL domain. An underlying assumption for most of these research efforts is the existence of a domain ontology. The second unspoken assumption follows that educators will build domain ontologies for their…

Overconfidence Produces Underachievement: Inaccurate Self Evaluations Undermine Students' Learning and Retention

ERIC Educational Resources Information Center

Dunlosky, John; Rawson, Katherine A.

2012-01-01

The function of accurately monitoring one's own learning is to support effective control of study that enhances learning. Although this link between monitoring accuracy and learning is intuitively plausible and is assumed by general theories of self-regulated learning, it has not received a great deal of empirical scrutiny and no study to date has…

Multinational Companies as a Source of Entrepreneurial Learning Examples from the It Sector in Ireland

ERIC Educational Resources Information Center

McKeon, Helen; Johnston, Kate; Henry, Colette

2004-01-01

Entrepreneurial learning has recently become a topic of significant interest, with academics and economists alike recognising that the success of any new business venture is closely linked to the learning and knowledge of the entrepreneur. To date, research into entrepreneurial learning and the specific ways in which entrepreneurs learn is…

Ontology Mappings to Improve Learning Resource Search

ERIC Educational Resources Information Center

Gasevic, Dragan; Hatala, Marek

2006-01-01

This paper proposes an ontology mapping-based framework that allows searching for learning resources using multiple ontologies. The present applications of ontologies in e-learning use various ontologies (eg, domain, curriculum, context), but they do not give a solution on how to interoperate e-learning systems based on different ontologies. The…

Implicit Learning of Semantic Preferences of Verbs

ERIC Educational Resources Information Center

Paciorek, Albertyna; Williams, John N.

2015-01-01

Previous studies of semantic implicit learning in language have only examined learning grammatical form-meaning connections in which learning could have been supported by prior linguistic knowledge. In this study we target the domain of verb meaning, specifically semantic preferences regarding novel verbs (e.g., the preference for a novel verb to…

An Interactive Learning Environment for Information and Communication Theory

ERIC Educational Resources Information Center

Hamada, Mohamed; Hassan, Mohammed

2017-01-01

Interactive learning tools are emerging as effective educational materials in the area of computer science and engineering. It is a research domain that is rapidly expanding because of its positive impacts on motivating and improving students' performance during the learning process. This paper introduces an interactive learning environment for…

Competence-Based Knowledge Structures for Personalised Learning

ERIC Educational Resources Information Center

Heller, Jurgen; Steiner, Christina; Hockemeyer, Cord; Albert, Dietrich

2006-01-01

Competence-based extensions of Knowledge Space Theory are suggested as a formal framework for implementing key features of personalised learning in technology-enhanced learning. The approach links learning objects and assessment problems to the relevant skills that are taught or required. Various ways to derive these skills from domain ontologies…

Exploring Learner Autonomy: Language Learning Locus of Control in Multilinguals

ERIC Educational Resources Information Center

Peek, Ron

2016-01-01

By using data from an online language learning beliefs survey (n?=?841), defining language learning experience in terms of participants' multilingualism, and using a domain-specific language learning locus of control (LLLOC) instrument, this article examines whether more experienced language learners can also be seen as more autonomous language…

Architecture for Building Conversational Agents that Support Collaborative Learning

ERIC Educational Resources Information Center

Kumar, R.; Rose, C. P.

2011-01-01

Tutorial Dialog Systems that employ Conversational Agents (CAs) to deliver instructional content to learners in one-on-one tutoring settings have been shown to be effective in multiple learning domains by multiple research groups. Our work focuses on extending this successful learning technology to collaborative learning settings involving two or…

Museum Learning: A Study of Motivation and Learning Achievement

ERIC Educational Resources Information Center

Wilde, Mathias; Urhahne, Detlef

2008-01-01

According to Reinmann-Rothmeier and Mandl (2001), learning environments should provide an ideal balance between constructivist and instructive elements. Most interesting for constructivist learning processes is the combination of the cognitive and the motivational domain. In an empirical study with 207 fifth-graders of the highest stratification…

Learning Dispositions and the Role of Mutual Engagement: Factors for Consideration in Educational Settings

ERIC Educational Resources Information Center

Duncan, Judith; Jones, Carolyn; Carr, Margaret

2008-01-01

This article describes an emerging theoretical framework for examining relationships between learning dispositions and learning architecture. Three domains of learning dispositions--resilience, reciprocity and imagination--are discussed in relation to the structures and processes of early childhood education settings and new entrant classrooms.…

Computer Proficiency for Online Learning: Factorial Invariance of Scores among Teachers

ERIC Educational Resources Information Center

Martin, Amy L.; Reeves, Todd D.; Smith, Thomas J.; Walker, David A.

2016-01-01

Online learning is variously employed in K-12 education, including for teacher professional development. However, the use of computer-based technologies for learning purposes assumes learner computer proficiency, making this construct an important domain of procedural knowledge in formal and informal online learning contexts. Addressing this…

Analyzing Teacher Narratives in Early Childhood Garden-Based Education

ERIC Educational Resources Information Center

Murakami, Christopher Daniel; Su-Russell, Chang; Manfra, Louis

2018-01-01

Learning gardens can provide dynamic learning and developmental experiences for young children. This case study of 12 early childhood teachers explores how teachers describe (1) learning across numerous school readiness domains and (2) how to support this learning by promoting opportunities for autonomy, relatedness, and competence. Participants…

Seeing Is as Good as Doing

ERIC Educational Resources Information Center

Osman, Magda

2008-01-01

Given the privileged status claimed for active learning in a variety of domains (visuomotor learning, causal induction, problem solving, education, skill learning), the present study examines whether action-based learning is a necessary, or a sufficient, means of acquiring the relevant skills needed to perform a task typically described as…

COLLAGE: A Collaborative Learning Design Editor Based on Patterns

ERIC Educational Resources Information Center

Hernandez-Leo, Davinia; Villasclaras-Fernandez, Eloy D.; Asensio-Perez, Juan I.; Dimitriadis, Yannis; Jorrin-Abellan, Ivan M.; Ruiz-Requies, Ines; Rubia-Avi, Bartolome

2006-01-01

This paper introduces "Collage", a high-level IMS-LD compliant authoring tool that is specialized for CSCL (Computer-Supported Collaborative Learning). Nowadays CSCL is a key trend in e-learning since it highlights the importance of social interactions as an essential element of learning. CSCL is an interdisciplinary domain, which…

Very Similar Spacing-Effect Patterns in Very Different Learning/Practice Domains

PubMed Central

Kornmeier, Jürgen; Spitzer, Manfred; Sosic-Vasic, Zrinka

2014-01-01

Temporally distributed (“spaced”) learning can be twice as efficient as massed learning. This “spacing effect” occurs with a broad spectrum of learning materials, with humans of different ages, with non-human vertebrates and also invertebrates. This indicates, that very basic learning mechanisms are at work (“generality”). Although most studies so far focused on very narrow spacing interval ranges, there is some evidence for a non-monotonic behavior of this “spacing effect” (“nonlinearity”) with optimal spacing intervals at different time scales. In the current study we focused both the nonlinearity aspect by using a broad range of spacing intervals and the generality aspect by using very different learning/practice domains: Participants learned German-Japanese word pairs and performed visual acuity tests. For each of six groups we used a different spacing interval between learning/practice units from 7 min to 24 h in logarithmic steps. Memory retention was studied in three consecutive final tests, one, seven and 28 days after the final learning unit. For both the vocabulary learning and visual acuity performance we found a highly significant effect of the factor spacing interval on the final test performance. In the 12 h-spacing-group about 85% of the learned words stayed in memory and nearly all of the visual acuity gain was preserved. In the 24 h-spacing-group, in contrast, only about 33% of the learned words were retained and the visual acuity gain dropped to zero. The very similar patterns of results from the two very different learning/practice domains point to similar underlying mechanisms. Further, our results indicate spacing in the range of 12 hours as optimal. A second peak may be around a spacing interval of 20 min but here the data are less clear. We discuss relations between our results and basic learning at the neuronal level. PMID:24609081

Age mapping and dating of monazite on the electron microprobe: Deconvoluting multistage tectonic histories

NASA Astrophysics Data System (ADS)

Williams, Michael L.; Jercinovic, Michael J.; Terry, Michael P.

1999-11-01

High-resolution X-ray mapping and dating of monazite on the electron microprobe are powerful geochronological tools for structural, metamorphic, and tectonic analysis. X-ray maps commonly show complex Th, U, and Pb zoning that reflects monazite growth and overgrowth events. Age maps constructed from the X-ray maps simplify the zoning and highlight age domains. Microprobe dating offers a rapid, in situ method for estimating ages of mapped domains. Application of these techniques has placed new constraints on the tectonic history of three areas. In western Canada, age mapping has revealed multiphase monazite, with older cores and younger rims, included in syntectonic garnet. Microprobe ages show that tectonism occurred ca. 1.9 Ga, 700 m.y. later than mylonitization in the adjacent Snowbird tectonic zone. In New Mexico, age mapping and dating show that the dominant fabric and triple-point metamorphism occurred during a 1.4 Ga reactivation, not during the 1.7 Ga Yavapai-Mazatzal orogeny. In Norway, monazite inclusions in garnet constrain high-pressure metamorphism to ca. 405 Ma, and older cores indicate a previously unrecognized component of ca. 1.0 Ga monazite. In all three areas, microprobe dating and age mapping have provided a critical textural context for geochronologic data and a better understanding of the complex age spectra of these multistage orogenic belts.

Assessing Neurophysiologic Markers for Training and Simulation to Develop Expertise in Complex Cognitive Tasks

DTIC Science & Technology

2010-09-01

analysis process is to categorize the goal according to (Gagné, 2005) domains of learning . These domains are: verbal information, intellectual...to terrain features. The ability to provide a clear verbal description of a unique feature is a learned task that may be separate from the...and experts differently. The process of verbally encoding information on location and providing this description may detract from the primary task of

Teaching Communication Skills to Medical and Pharmacy Students Through a Blended Learning Course.

PubMed

Hess, Rick; Hagemeier, Nicholas E; Blackwelder, Reid; Rose, Daniel; Ansari, Nasar; Branham, Tandy

2016-05-25

Objective. To evaluate the impact of an interprofessional blended learning course on medical and pharmacy students' patient-centered interpersonal communication skills and to compare precourse and postcourse communication skills across first-year medical and second-year pharmacy student cohorts. Methods. Students completed ten 1-hour online modules and participated in five 3-hour group sessions over one semester. Objective structured clinical examinations (OSCEs) were administered before and after the course and were evaluated using the validated Common Ground Instrument. Nonparametric statistical tests were used to examine pre/postcourse domain scores within and across professions. Results. Performance in all communication skill domains increased significantly for all students. No additional significant pre/postcourse differences were noted across disciplines. Conclusion. Students' patient-centered interpersonal communication skills improved across multiple domains using a blended learning educational platform. Interview abilities were embodied similarly between medical and pharmacy students postcourse, suggesting both groups respond well to this form of instruction.

Ranking Medical Terms to Support Expansion of Lay Language Resources for Patient Comprehension of Electronic Health Record Notes: Adapted Distant Supervision Approach.

PubMed

Chen, Jinying; Jagannatha, Abhyuday N; Fodeh, Samah J; Yu, Hong

2017-10-31

Medical terms are a major obstacle for patients to comprehend their electronic health record (EHR) notes. Clinical natural language processing (NLP) systems that link EHR terms to lay terms or definitions allow patients to easily access helpful information when reading through their EHR notes, and have shown to improve patient EHR comprehension. However, high-quality lay language resources for EHR terms are very limited in the public domain. Because expanding and curating such a resource is a costly process, it is beneficial and even necessary to identify terms important for patient EHR comprehension first. We aimed to develop an NLP system, called adapted distant supervision (ADS), to rank candidate terms mined from EHR corpora. We will give EHR terms ranked as high by ADS a higher priority for lay language annotation-that is, creating lay definitions for these terms. Adapted distant supervision uses distant supervision from consumer health vocabulary and transfer learning to adapt itself to solve the problem of ranking EHR terms in the target domain. We investigated 2 state-of-the-art transfer learning algorithms (ie, feature space augmentation and supervised distant supervision) and designed 5 types of learning features, including distributed word representations learned from large EHR data for ADS. For evaluating ADS, we asked domain experts to annotate 6038 candidate terms as important or nonimportant for EHR comprehension. We then randomly divided these data into the target-domain training data (1000 examples) and the evaluation data (5038 examples). We compared ADS with 2 strong baselines, including standard supervised learning, on the evaluation data. The ADS system using feature space augmentation achieved the best average precision, 0.850, on the evaluation set when using 1000 target-domain training examples. The ADS system using supervised distant supervision achieved the best average precision, 0.819, on the evaluation set when using only 100 target-domain training examples. The 2 ADS systems both performed significantly better than the baseline systems (P<.001 for all measures and all conditions). Using a rich set of learning features contributed to ADS's performance substantially. ADS can effectively rank terms mined from EHRs. Transfer learning improved ADS's performance even with a small number of target-domain training examples. EHR terms prioritized by ADS were used to expand a lay language resource that supports patient EHR comprehension. The top 10,000 EHR terms ranked by ADS are available upon request. ©Jinying Chen, Abhyuday N Jagannatha, Samah J Fodeh, Hong Yu. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 31.10.2017.

Growing pains and pleasures: how emotional learning guides development.

PubMed

Nelson, Eric E; Lau, Jennifer Y F; Jarcho, Johanna M

2014-02-01

The nervous system promotes adaptive responding to myriad environmental stimuli by ascribing emotion to specific stimulus domains. This affects the salience of different stimuli, facilitates learning, and likely involves the amygdala. Recent studies suggest a strong homology between adaptive responses that result from learning and those that emerge during development. As in motivated learning, developmental studies have found the salience of different classes of stimulus (e.g., peers) undergoes marked fluctuation across maturation and may involve differential amygdala engagement. In this review, by highlighting the importance of particular stimulus categories during sensitive periods of development, we suggest that variability in amygdala response to different stimulus domains has an active and functional role in shaping emerging cortical circuits across development. Published by Elsevier Ltd.

Growing Pains and Pleasures: How Emotional Learning Guides Development

PubMed Central

Nelson, Eric E.; Lau, Jennifer Y.F.; Jarcho, Johanna M.

2014-01-01

SUMMARY The nervous system promotes adaptive responding to myriad environmental stimuli by ascribing emotion to specific stimulus domains. This affects the salience of different stimuli, facilitates learning, and likely involves the amygdala. Recent studies suggest a strong homology between adaptive responses that result from learning and those that emerge during development. As in motivated learning, developmental studies have found the salience of different classes of stimuli (eg peers) undergoes marked fluctuation across maturation and may involve differential amygdala engagement. We suggest that variability in amygdala response to different stimulus domains may play an active and functional role in shaping emerging cortical circuits across development by highlighting the importance of particular stimulus categories during sensitive periods of development. PMID:24405846

Rapid e-Learning Tools Selection Process for Cognitive and Psychomotor Learning Objectives

ERIC Educational Resources Information Center

Ku, David Tawei; Huang, Yung-Hsin

2012-01-01

This study developed a decision making process for the selection of rapid e-learning tools that could match different learning domains. With the development of the Internet, the speed of information updates has become faster than ever. E-learning has rapidly become the mainstream for corporate training and academic instruction. In order to reduce…

The Effect of Prompting to Students with Different Learning Styles

ERIC Educational Resources Information Center

Papadopoulos, Pantelis M.; Demetriadis, Stavros N.; Stamelos, Ioannis G.; Tsoukalas, Ioannis A.

2010-01-01

Purpose: The purpose of this paper is to explore the impact of question prompts on student learning in relation to their learning styles. The context of the study is technology-enhanced learning in an ill-structured domain. Design/methodology/approach: The study conditions were the same for all the students in the four learning style groups.…

Supporting Case-Based Learning in Information Security with Web-Based Technology

ERIC Educational Resources Information Center

He, Wu; Yuan, Xiaohong; Yang, Li

2013-01-01

Case-based learning has been widely used in many disciplines. As an effective pedagogical method, case-based learning is also being used to support teaching and learning in the domain of information security. In this paper, we demonstrate case-based learning in information security by sharing our experiences in using a case study to teach security…

Designing On-Demand Education for Simultaneous Development of Domain-Specific and Self-Directed Learning Skills

ERIC Educational Resources Information Center

Taminiau, E. M. C.; Kester, L.; Corbalan, G.; Spector, J. M.; Kirschner, P. A.; Van Merriënboer, J. J. G.

2015-01-01

On-demand education enables individual learners to choose their learning pathways according to their own learning needs. They must use self-directed learning (SDL) skills involving self-assessment and task selection to determine appropriate pathways for learning. Learners who lack these skills must develop them because SDL skills are prerequisite…

Science of Learning Is Learning of Science: Why We Need a Dialectical Approach to Science Education Research

ERIC Educational Resources Information Center

Roth, Wolff-Michael

2012-01-01

Research on learning science in informal settings and the formal (sometimes experimental) study of learning in classrooms or psychological laboratories tend to be separate domains, even drawing on different theories and methods. These differences make it difficult to compare knowing and learning observed in one paradigm/context with those observed…

Technically Speaking: Transforming Language Learning through Virtual Learning Environments (MOOs).

ERIC Educational Resources Information Center

von der Emde, Silke; Schneider, Jeffrey; Kotter, Markus

2001-01-01

Draws on experiences from a 7-week exchange between students learning German at an American college and advanced students of English at a German university. Maps out the benefits to using a MOO (multiple user domains object-oriented) for language learning: a student-centered learning environment structured by such objectives as peer teaching,…

The Effect of Teacher Performance in Implementation of The 2013 Curriculum Toward Chemistry Learning Achievement

NASA Astrophysics Data System (ADS)

Dewi, L. P.; Djohar, A.

2018-04-01

This research is a study about implementation of the 2013 Curriculum on Chemistry subject. This study aims to determine the effect of teacher performance toward chemistry learning achievement. The research design involves the independent variable, namely the performance of Chemistry teacher, and the dependent variable that is Chemistry learning achievement which includes the achievement in knowledge and skill domain. The subject of this research are Chemistry teachers and High School students in Bandung City. The research data is obtained from questionnaire about teacher performance assessed by student and Chemistry learning achievement from the students’ report. Data were analyzed by using MANOVA test. The result of multivariate significance test shows that there is a significant effect of teacher performance toward Chemistry learning achievement in knowledge and skill domain with medium effect size.

Concept Mapping Assessment of Media Assisted Learning in Interdisciplinary Science Education

NASA Astrophysics Data System (ADS)

Schaal, Steffen; Bogner, Franz X.; Girwidz, Raimund

2010-05-01

Acquisition of conceptual knowledge is a central aim in science education. In this study we monitored an interdisciplinary hypermedia assisted learning unit on hibernation and thermodynamics based on cooperative learning. We used concept mapping for the assessment, applying a pre-test/post-test design. In our study, 106 9th graders cooperated by working in pairs ( n = 53) for six lessons. As an interdisciplinary learning activity in such complex knowledge domains has to combine many different aspects, we focused on long-term knowledge. Learners working cooperatively in dyads constructed computer-supported concept maps which were analysed by specific software. The data analysis encompassed structural aspects of the knowledge corresponding to a target reference map. After the learning unit, the results showed the acquisition of higher-order domain-specific knowledge structures which indicates successful interdisciplinary learning through the hypermedia learning environment. The benefit of using a computer-assisted concept mapping assessment for research in science education, and in science classrooms is considered.

Limited angle CT reconstruction by simultaneous spatial and Radon domain regularization based on TV and data-driven tight frame

NASA Astrophysics Data System (ADS)

Zhang, Wenkun; Zhang, Hanming; Wang, Linyuan; Cai, Ailong; Li, Lei; Yan, Bin

2018-02-01

Limited angle computed tomography (CT) reconstruction is widely performed in medical diagnosis and industrial testing because of the size of objects, engine/armor inspection requirements, and limited scan flexibility. Limited angle reconstruction necessitates usage of optimization-based methods that utilize additional sparse priors. However, most of conventional methods solely exploit sparsity priors of spatial domains. When CT projection suffers from serious data deficiency or various noises, obtaining reconstruction images that meet the requirement of quality becomes difficult and challenging. To solve this problem, this paper developed an adaptive reconstruction method for limited angle CT problem. The proposed method simultaneously uses spatial and Radon domain regularization model based on total variation (TV) and data-driven tight frame. Data-driven tight frame being derived from wavelet transformation aims at exploiting sparsity priors of sinogram in Radon domain. Unlike existing works that utilize pre-constructed sparse transformation, the framelets of the data-driven regularization model can be adaptively learned from the latest projection data in the process of iterative reconstruction to provide optimal sparse approximations for given sinogram. At the same time, an effective alternating direction method is designed to solve the simultaneous spatial and Radon domain regularization model. The experiments for both simulation and real data demonstrate that the proposed algorithm shows better performance in artifacts depression and details preservation than the algorithms solely using regularization model of spatial domain. Quantitative evaluations for the results also indicate that the proposed algorithm applying learning strategy performs better than the dual domains algorithms without learning regularization model

Activity and Participation Characteristics of Adults with Learning Disabilities - A Systematic Review

PubMed Central

Sharfi, Kineret; Rosenblum, Sara

2014-01-01

Background ‘Learning disabilities’ (LD) refer to a wide group of neurological disorders caused by deficits in the central nervous system which influence the individual's ability to maintain-, process or convey information to others in an efficient way. A worldwide discussion about the definitions of LD continues while a conceptual framework for studying the diverse life outcomes of adults with LD is still missing. Objective The aim was to review the literature on the activity and participation of adults with LD based on the International Classification of Functioning, Disability and Health (ICF) concepts. Methods “PsychInfo”, “Eric” and “PubMed” were searched for relevant literature according to the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). After a three-stage process, 62 articles relevant for domains of activity and participation of adults with LD were included in the review. Results Thirty-two articles focused on the domain of major life areas of education, work and employment and twelve articles focused on the domain of learning and applying knowledge. Limitations in activity and participation of the population with LD in these domains are recognized and discussed. Eighteen additional articles demonstrated that adults with LD confront difficulties in various life domains (e.g., communication, interpersonal interactions, mobility, and domestic life), however literature concerning these domains is scarce. Conclusions The ICF can be useful for further exploration of activity and participation characteristics of adults with LD in various life domains. Such exploration is required in order to gain a wider perspective of their functional characteristics and daily needs. PMID:25184315

Student evaluation of clickers in a combined dental and dental hygiene periodontology course.

PubMed

Satheesh, Keerthana M; Saylor-Boles, Catherine D; Rapley, John W; Liu, Ying; Gadbury-Amyot, Cynthia C

2013-10-01

The purpose of this report is to describe the general use of clickers as an active learning tool and how they were used in teaching a combined periodontology course for second-year dental and junior dental hygiene students. A survey was used to capture student perceptions following completion of the course. Specific domains were active learning, improved performance, and expectations. The survey response rate was 94.5 percent (121/128). Descriptive analyses showed that, in the domain of active learning, 102 (84.3 percent) agreed/strongly agreed that the use of clickers made the lectures more interactive; sixty-six (54.5 percent) agreed/strongly agreed that the clickers made them focus; and ninety-two (76 percent) agreed/strongly agreed that the clickers encouraged active participation. In the domain regarding improved performance, sixty-three (52 percent) agreed/ strongly agreed that the review sessions utilizing clickers helped them prepare for tests. In the domain of expectations, ninety-three (76.9 percent) had a better idea of what to expect on the examination due to the use of clickers, and seventy-three (60.3 percent) thought that the clickers should be used in future semesters for this class. In addition, faculty members appreciated the greater participation afforded through the use of clickers to obtain a better understanding of the students' grasp of course content. Learning theory suggests that students must actively engage in the learning process in order for meaningful learning in the form of critical thinking and problem-solving to take place. In this study, students confirmed that the use of clicker technology encouraged their active participation in a periodontology course.

Approximation algorithms for scheduling unrelated parallel machines with release dates

NASA Astrophysics Data System (ADS)

Avdeenko, T. V.; Mesentsev, Y. A.; Estraykh, I. V.

2017-01-01

In this paper we propose approaches to optimal scheduling of unrelated parallel machines with release dates. One approach is based on the scheme of dynamic programming modified with adaptive narrowing of search domain ensuring its computational effectiveness. We discussed complexity of the exact schedules synthesis and compared it with approximate, close to optimal, solutions. Also we explain how the algorithm works for the example of two unrelated parallel machines and five jobs with release dates. Performance results that show the efficiency of the proposed approach have been given.

Organizational culture in cardiovascular care in Chinese hospitals: a descriptive cross-sectional study.

PubMed

Yin, Emily S; Downing, Nicholas S; Li, Xi; Singer, Sara J; Curry, Leslie A; Li, Jing; Krumholz, Harlan M; Jiang, Lixin

2015-12-21

Organizational learning, the process by which a group changes its behavior in response to newly acquired knowledge, is critical to outstanding organizational performance. In hospitals, strong organizational learning culture is linked with improved health outcomes for patients. This study characterizes the organizational learning culture of hospitals in China from the perspective of a cardiology service. Using a modified Abbreviated Learning Organization Survey (27 questions), we characterized organizational learning culture in a nationally representative sample of 162 Chinese hospitals, selecting 2 individuals involved with cardiovascular care at each hospital. Responses were analyzed at the hospital level by calculating the average of the two responses to each question. Responses were categorized as positive if they were 5+ on a 7-point scale or 4+ on a 5-point scale. Univariate and multiple regression analyses were used to assess the relationship between selected hospital characteristics and perceptions of organizational learning culture. Of the 324 participants invited to take the survey, 316 responded (98 % response rate). Perceptions of organizational learning culture varied among items, among domains, and both among and within hospitals. Overall, the median proportion of positive responses was 82 % (interquartile range = 59 % to 93 %). "Training," "Performance Monitoring," and "Leadership that Reinforces Learning" were characterized as the most favorable domains, while "Time for Reflection" was the least favorable. Multiple regression analyses showed that region was the only factor significantly correlated with overall positive response rate. This nationally representative survey demonstrated variation in hospital organizational learning culture among hospitals in China. The variation was not substantially explained by hospital characteristics. Organizational learning culture domains with lower positive response rates reveal important areas for improvement.

78 FR 21275 - Station Blackout Mitigation Strategies

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-10

... stemming from the NRC's lessons-learned efforts associated with the March 2011 Fukushima Dai-ichi Nuclear Power Plant accident in Japan. DATES: Submit comments by May 28, 2013. Comments received after this date...

Learning styles and academic achievement among undergraduate medical students in Thailand.

PubMed

Jiraporncharoen, Wichuda; Angkurawaranon, Chaisiri; Chockjamsai, Manoch; Deesomchok, Athavudh; Euathrongchit, Juntima

2015-01-01

This study aimed to explore the associations between learning styles and high academic achievement and to ascertain whether the factors associated with high academic achievement differed between preclinical and clinical students. A survey was conducted among undergraduate medical students in Chiang Mai University, Thailand. The Index of Learning Styles questionnaire was used to assess each student's learning style across four domains. High academic achievement was defined as a grade point average of at least 3.0. Of the 1,248 eligible medical students, 1,014 (81.3%) participated. Learning styles differed between the preclinical and clinical students in the active/reflective domain. A sequential learning style was associated with high academic achievement in both preclinical and clinical students. A reflective learning style was only associated with high academic achievement among preclinical students. The association between learning styles and academic achievement may have differed between preclinical and clinical students due to different learning content and teaching methods. Students should be encouraged to be flexible in their own learning styles in order to engage successfully with various and changing teaching methods across the curriculum. Instructors should be also encouraged to provide a variety of teaching materials and resources to suit different learning styles.

A Mapping from the Human Factors Analysis and Classification System (DOD-HFACS) to the Domains of Human Systems Integration (HSI)

DTIC Science & Technology

2009-11-01

Equation Chapter 1 Section 1 A MAPPING FROM THE HUMAN FACTORS ANALYSIS AND CLASSIFICATION SYSTEM (DOD...OMB control number. 1. REPORT DATE NOV 2009 2. REPORT TYPE 3. DATES COVERED 4. TITLE AND SUBTITLE A Mapping from the Human Factors Analysis ...7 The Human Factors Analysis and Classification System .................................................. 7 Mapping of DoD

Supporting Development of Satellite's Guidance Navigation and Control Software: A Product Line Approach

NASA Technical Reports Server (NTRS)

McComas, David; Stark, Michael; Leake, Stephen; White, Michael; Morisio, Maurizio; Travassos, Guilherme H.; Powers, Edward I. (Technical Monitor)

2000-01-01

The NASA Goddard Space Flight Center Flight Software Branch (FSB) is developing a Guidance, Navigation, and Control (GNC) Flight Software (FSW) product line. The demand for increasingly more complex flight software in less time while maintaining the same level of quality has motivated us to look for better FSW development strategies. The GNC FSW product line has been planned to address the core GNC FSW functionality very similar on many recent low/near Earth missions in the last ten years. Unfortunately these missions have not accomplished significant drops in development cost since a systematic approach towards reuse has not been adopted. In addition, new demands are continually being placed upon the FSW which means the FSB must become more adept at providing GNC FSW functionality's core so it can accommodate additional requirements. These domain features together with engineering concepts are influencing the specification, description and evaluation of FSW product line. Domain engineering is the foundation for emerging product line software development approaches. A product line is 'A family of products designed to take advantage of their common aspects and predicted variabilities'. In our product line approach, domain engineering includes the engineering activities needed to produce reusable artifacts for a domain. Application engineering refers to developing an application in the domain starting from reusable artifacts. The focus of this paper is regarding the software process, lessons learned and on how the GNC FSW product line manages variability. Existing domain engineering approaches do not enforce any specific notation for domain analysis or commonality and variability analysis. Usually, natural language text is the preferred tool. The advantage is the flexibility and adapt ability of natural language. However, one has to be ready to accept also its well-known drawbacks, such as ambiguity, inconsistency, and contradictions. While most domain analysis approaches are functionally oriented, the idea of applying the object-oriented approach in domain analysis is not new. Some authors propose to use UML as the notation underlying domain analysis. Our work is based on the same idea of merging UML and domain analysis. Further, we propose a few extensions to UML in order to express variability, and we define precisely their semantics so that a tool can support them. The extensions are designed to be implemented on the API of a popular industrial CASE tool, with obvious advantages in cost and availability of tool support. The paper outlines the product line processes and identifies where variability must be addressed. Then it describes the product line products with respect to how they accommodate variability. The Celestial Body subdomain is used as a working example. Our results to date are summarized and plans for the future are described.

P- T- t constraints on the development of the Doi Inthanon metamorphic core complex domain and implications for the evolution of the western gneiss belt, northern Thailand

NASA Astrophysics Data System (ADS)

Macdonald, A. S.; Barr, S. M.; Miller, B. V.; Reynolds, P. H.; Rhodes, B. P.; Yokart, B.

2010-01-01

The western gneiss belt in northern Thailand is exposed within two overlapping Cenozoic structural domains: the extensional Doi Inthanon metamorphic core complex domain located west of the Chiang Mai basin, and the Mae Ping strike-slip fault domain located west of the Tak batholith. New P- T estimates and U-Pb and 40Ar/ 39Ar age determinations from the Doi Inthanon domain show that the gneiss there records a complex multi-stage history that can be represented by a clockwise P- T- t path. U-Pb zircon and titanite dating of mylonitic calc-silicate gneiss from the Mae Wang area of the complex indicates that the paragneissic sequence experienced high-grade, medium-pressure metamorphism (M1) in the Late Triassic - Early Jurassic (ca. 210 Ma), in good agreement with previously determined zircon ages from the underlying core orthogneiss exposed on Doi Inthanon. Late Cretaceous monazite ages of 84 and 72 Ma reported previously from the core orthogneiss are attributed to a thermal overprint (M2) to upper-amphibolite facies in the sillimanite field. U-Pb zircon and monazite dating of granitic mylonite from the Doi Suthep area of the complex provides an upper age limit of 40 Ma (Late Eocene) for the early stage(s) of development of the actual core complex, by initially ductile, low-angle extensional shearing under lower amphibolite-facies conditions (M3), accompanied by near-isothermal diapiric rise and decompression melting. 40Ar/ 39Ar laserprobe dating of muscovite from both Doi Suthep and Doi Inthanon provided Miocene ages of ca. 26-15 Ma, representing cooling through the ca. 350 °C isotherm and marking late-stage development of the core complex by detachment faulting of the cover rocks and isostatic uplift of the sheared core zone and mantling gneisses in the footwall. Similarities in the thermochronology of high-grade gneisses exposed in the core complex and shear zone domains in the western gneiss belt of northern Thailand (and also in northern Vietnam, Laos, Yunnan, and central Myanmar) suggest a complex regional response to indentation of Southeast Asia by India.

A Model for In-Service Teacher Learning in the Context of an Innovation

ERIC Educational Resources Information Center

Coenders, Fer; Terlouw, Cees

2015-01-01

When curricula change, teachers have to bring their knowledge and beliefs up to date. Two aspects can be distinguished: "what" do teachers learn and "how" is it learned. Two groups of teachers were involved during the preparation of a new chemistry curriculum. One group developed student learning material and subsequently…

Reflecting on Quality Learning in a Student Writing Experience Supported by Technology.

ERIC Educational Resources Information Center

Ellis, Robert

With rapid developments in information technology in society being mirrored in the use of new learning technologies in universities, research into the quality of technologically-supported learning is essential. To date, research into new learning technologies has provided us with valuable knowledge that includes the theories behind their design,…

A Comparison between Paper-Based and Online Learning in Higher Education

ERIC Educational Resources Information Center

Emerson, Lisa; MacKay, Bruce

2011-01-01

To date researchers have had difficulty establishing reliable conclusions in studies comparing traditional forms of learning (eg paper-based or classroom based) vs online learning in relation to student learning outcomes; no consistent results have emerged, and many studies have not been controlled for factors other than lesson mode. This paper…

Rural Learning: A Practical Guide to Developing Learning Opportunities in the Countryside.

ERIC Educational Resources Information Center

Payne, John

This guide to rural learning is intended to help those developing learning opportunities in the United Kingdom countryside--teachers, program organizers, project and development workers, and health and housing workers. Section 1 supplies up-to-date facts and figures and useful information about living in the rural context. It highlights issues…

Beyond Smarter: Mediated Learning and the Brain's Capacity for Change

ERIC Educational Resources Information Center

Feuerstein, Reuven; Feuerstein, Refael; Falik, Louis H.

2010-01-01

Originally developed to help students overcome learning obstacles created by emotional trauma or neurobiological learning disabilities, Reuven Feuerstein's work is now used in major cities around the world to support improved thinking and learning by all students. This book is the most up-to-date summary of his thinking and includes accessible…

Students' perception of the learning environment in a distributed medical programme

PubMed Central

Veerapen, Kiran; McAleer, Sean

2010-01-01

Background The learning environment of a medical school has a significant impact on students' achievements and learning outcomes. The importance of equitable learning environments across programme sites is implicit in distributed undergraduate medical programmes being developed and implemented. Purpose To study the learning environment and its equity across two classes and three geographically separate sites of a distributed medical programme at the University of British Columbia Medical School that commenced in 2004. Method The validated Dundee Ready Educational Environment Survey was sent to all students in their 2nd and 3rd year (classes graduating in 2009 and 2008) of the programme. The domains of the learning environment surveyed were: students' perceptions of learning, students' perceptions of teachers, students' academic self-perceptions, students' perceptions of the atmosphere, and students' social self-perceptions. Mean scores, frequency distribution of responses, and inter- and intrasite differences were calculated. Results The perception of the global learning environment at all sites was more positive than negative. It was characterised by a strongly positive perception of teachers. The work load and emphasis on factual learning were perceived negatively. Intersite differences within domains of the learning environment were more evident in the pioneer class (2008) of the programme. Intersite differences consistent across classes were largely related to on-site support for students. Conclusions Shared strengths and weaknesses in the learning environment at UBC sites were evident in areas that were managed by the parent institution, such as the attributes of shared faculty and curriculum. A greater divergence in the perception of the learning environment was found in domains dependent on local arrangements and social factors that are less amenable to central regulation. This study underlines the need for ongoing comparative evaluation of the learning environment at the distributed sites and interaction between leaders of these sites. PMID:20922033

Quantifying the timescales of Archean UHT metamorphism through U-Pb monazite and zircon petrochronology

NASA Astrophysics Data System (ADS)

Guevara, V.; MacLennan, S. A.; Schoene, B.; Dragovic, B.; Caddick, M. J.; Kylander-Clark, A. R.; Couëslan, C. G.

2016-12-01

Unraveling the timescales of metamorphism is crucial to understanding the mechanisms behind mass/heat transfer through Earth's crust. Though such mechanisms and their durations are becoming well constrained in modern (Phanerozoic) settings, the drivers of metamorphism in the ancient geologic record remain more enigmatic. The development of accessory phase petrochronology has allowed metamorphic evolution to be closely linked to isotopic dates, ultimately improving quantification of metamorphic durations. While in-situ petrochronological methods preserve textural and spatial context, they often lack the temporal resolution required to accurately quantify metamorphic duration in Archean terranes. Here we combine in-situ U-Pb monazite (mnz) and zircon (zrn) laser ablation split-stream (LASS) and high-precision ID-TIMS-TEA petrochronology of distinct grain domains to resolve the timescales of ultrahigh temperature (UHT) metamorphism in the Archean Pikwitonei granulite domain (PGD). The PGD encompasses >1.5x105 km2 of granulite-facies rocks on the NW edge of the Superior Province. Themodynamic modelling of a pelite from the western part of the PGD suggests peak P-T conditions of >8 kbar, 900-940 °C and UHT decompression to 8 kbar followed by cooling. LASS analysis of zrn inclusions in garnet (grt) yields a date of 2701 Ma, with Ti in zrn thermometry yielding T of 800-900 °C. LASS analysis of mnz yields dates of 2720-2680 Ma for low HREE domains with no to shallow negative Eu anomalies, suggestive of growth during plagioclase (plg) breakdown and grt stability. ID-TIMS analysis of a mnz fragment with a strong negative Eu anomaly, suggestive of growth during plg stability, gives a concordant 207Pb/206Pb date of 2666 Ma, consistent with LASS results of 2660-2640 Ma for chemically similar domains. ID-TIMS analyses of zrn rims yield a range of 207Pb/206Pb dates from 2671 to 2656 Ma (±<1 Ma). Ti in zrn yields 800 °C for these rims, indicating they grew at similar T. Together, these data indicate a metamorphic cycle in the PGD to/from UHT over a minimum of 35 Ma, with at least 12 Ma of slow cooling near 800 °C in the lower crust following UHT decompression. This evolution is inconsistent with punctuated thermal pulses due to focused fluid flow or magmatism, instead requiring a long-lived source of crustal heating.

eLearning in the Workplace versus eLearning in Higher Education

ERIC Educational Resources Information Center

Daneshgar, Farhad; Van Toorn, Christine

2009-01-01

Great emphasis and recognition has been given to the potential of lifelong learning in the new millennium and the vast body of research on eLearning in Higher Education. However, to-date little research has been undertaken to review eLearning in the workplace. The present study aims to fill this gap to some degree by conducting a comparative…

Creativity Doesn't Develop in a Vacuum

ERIC Educational Resources Information Center

Barbot, Baptiste; Baer, John

2016-01-01

The skills, knowledge, attitudes, motivations, and personality traits that lead to creative thinking and creative behavior do not exist--and do not develop--in a vacuum. They are inextricably tied to content, to domains, in particular, and they therefore vary by domains. The more we learn about creativity, the more we discover how domain specific…

Learning Domains and the Process of Creativity

ERIC Educational Resources Information Center

Reid, Anna; Petocz, Peter

2004-01-01

Creativity is viewed in different ways in different disciplines: in education it is called "innovation", in business it is "entrepreneurship", in mathematics it is often equated with "problem solving", and in music it is "performance" or "composition". A creative product in different domains is measured against the norms of that domain, with its…

Domain Specificity and Generality of Epistemic Cognitions: Issues in Assessment

ERIC Educational Resources Information Center

Owen, Jesse J.

2011-01-01

As administers in higher education search for learning outcome measures, the assessment of epistemic cognitions, or how students critically think and reason about real-world issues, is paramount. The current study examined if students' expertise in a domain of study (i.e., domain specificity) influenced their scores on an empirically supported…

Teaching Through Interactions in Secondary School Classrooms: Revisiting the Factor Structure and Practical Application of the Classroom Assessment Scoring System–Secondary

PubMed Central

Hafen, Christopher A.; Hamre, Bridget K.; Allen, Joseph P.; Bell, Courtney A.; Gitomer, Drew H.; Pianta, Robert C.

2017-01-01

Valid measurement of how students’ experiences in secondary school classrooms lead to gains in learning requires a developmental approach to conceptualizing classroom processes. This article presents a potentially useful theoretical model, the Teaching Through Interactions framework, which posits teacher-student interactions as a central driver for student learning and that teacher-student interactions can be organized into three major domains. Results from 1,482 classrooms provide evidence for distinct emotional, organizational, and instructional domains of teacher-student interaction. It also appears that a three-factor structure is a better fit to observational data than alternative one- and two-domain models of teacher-student classroom interactions, and that the three-domain structure is generalizable from 6th through 12th grade. Implications for practitioners, stakeholders, and researchers are discussed. PMID:28232770

Epithelium-Stroma Classification via Convolutional Neural Networks and Unsupervised Domain Adaptation in Histopathological Images.

PubMed

Huang, Yue; Zheng, Han; Liu, Chi; Ding, Xinghao; Rohde, Gustavo K

2017-11-01

Epithelium-stroma classification is a necessary preprocessing step in histopathological image analysis. Current deep learning based recognition methods for histology data require collection of large volumes of labeled data in order to train a new neural network when there are changes to the image acquisition procedure. However, it is extremely expensive for pathologists to manually label sufficient volumes of data for each pathology study in a professional manner, which results in limitations in real-world applications. A very simple but effective deep learning method, that introduces the concept of unsupervised domain adaptation to a simple convolutional neural network (CNN), has been proposed in this paper. Inspired by transfer learning, our paper assumes that the training data and testing data follow different distributions, and there is an adaptation operation to more accurately estimate the kernels in CNN in feature extraction, in order to enhance performance by transferring knowledge from labeled data in source domain to unlabeled data in target domain. The model has been evaluated using three independent public epithelium-stroma datasets by cross-dataset validations. The experimental results demonstrate that for epithelium-stroma classification, the proposed framework outperforms the state-of-the-art deep neural network model, and it also achieves better performance than other existing deep domain adaptation methods. The proposed model can be considered to be a better option for real-world applications in histopathological image analysis, since there is no longer a requirement for large-scale labeled data in each specified domain.

Bidirectional Transfer between Metaphorical Related Domains in Implicit Learning of Form-Meaning Connections

PubMed Central

Yang, Zhiliang; Dienes, Zoltan

2013-01-01

People can implicitly learn a connection between linguistic forms and meanings, for example between specific determiners (e.g. this, that…) and the type of nouns to which they apply. Li et al (2013) recently found that transfer of form-meaning connections from a concrete domain (height) to an abstract domain (power) was achieved in a metaphor-consistent way without awareness, showing that unconscious knowledge can be abstract and flexibly deployed. The current study aims to determine whether people transfer knowledge of form-meaning connections not only from a concrete domain to an abstract one, but also vice versa, consistent with metaphor representation being bi-directional. With a similar paradigm as used by Li et al, participants learnt form- meaning connections of different domains (concrete vs. abstract) and then were tested on two kinds of generalizations (same and different domain generalization). As predicted, transfer of form-meaning connections occurred bidirectionally when structural knowledge was unconscious. Moreover, the present study also revealed that more transfer occurred between metaphorically related domains when judgment knowledge was conscious (intuition) rather than unconscious (guess). Conscious and unconscious judgment knowledge may have different functional properties. PMID:23844159

National Conference on Student & Scientist Partnerships

NASA Astrophysics Data System (ADS)

Barstow, D.

2001-05-01

Science education is turning an exciting corner with the development of a new class of projects called Student and Scientist Partnerships for authentic research. Examples include GLOBE, Hands-On Universe and EarthKAM. These projects engage students as learners and as participants in authentic research.Through such projects scientists acquire new research partners. At the same time, students experience real science, learning up-to-date science content and developing essential investigation skills. To better understand the nature and potential of these partnerships, an invitational conference was held in Washington, D.C.,from October 23-25, 1996. The conference, funded by the National Science Foundation and coordinated by TERC and the Concord Consortium, brought together 60 leaders in science and education who have research backgrounds, practical experience, or a high interest in Student, Scientists & Partnerships. The participants confirmed that this shift from the "student as recipient" to the "student as partner" model can be of real and substantive benefit for both the scientists and the students. The primary and most obvious benefits for the students are the excitement of doing authentic science, a new context for hands-on experiential learning, and the linkage of school learning with the "real world." For the scientists, the primary benefits are the help of student partners who enable the scientists to do research that might not otherwise be possible and the personal rewards of supporting education. Beyond these primary benefits, however, is a secondary and perhaps deeper level of benefits, resulting from the cross-fertilization between these two rich cultures. In each partnership, it helps to recognize and articulate what I call "the three authentics". Authentic Science-The science must be real science. It must contribute new knowledge. The research must be central to the scientists' work, and the student participation must contribute in a meaningful way to this research. Authentic Education-The learning experience for the students must build on "best practice" in education. Students should not simply be "data robots" for the scientists. Students should also do their own related investigations, so that they participate in effective inquiry-based learning, developing both content knowledge and skills of scientific investigation. The fact that they are contributing to the scientists' research is an exciting and compelling context for their learning, but it cannot be the only learning. Authentic Partnership-The partnership among the scientists, students and teachers must be a real partnership. Each partner must have a sincere and personal desire to participate in the partnership an enlightened self-interest. Each must also have a respect for the other's domain and a willingness to learn more about it. Neither partner can blindly relinquish its own core values. Each should, however, be prepared for new ideas and a few paradigm shifts, both in his or her perception of the other's domain and even in one's own field.

Impaired cognitive plasticity and goal-directed control in adolescent obsessive-compulsive disorder.

PubMed

Gottwald, Julia; de Wit, Sanne; Apergis-Schoute, Annemieke M; Morein-Zamir, Sharon; Kaser, Muzaffer; Cormack, Francesca; Sule, Akeem; Limmer, Winifred; Morris, Anna Conway; Robbins, Trevor W; Sahakian, Barbara J

2018-01-22

Youths with obsessive-compulsive disorder (OCD) experience severe distress and impaired functioning at school and at home. Critical cognitive domains for daily functioning and academic success are learning, memory, cognitive flexibility and goal-directed behavioural control. Performance in these important domains among teenagers with OCD was therefore investigated in this study. A total of 36 youths with OCD and 36 healthy comparison subjects completed two memory tasks: Pattern Recognition Memory (PRM) and Paired Associates Learning (PAL); as well as the Intra-Extra Dimensional Set Shift (IED) task to quantitatively gauge learning as well as cognitive flexibility. A subset of 30 participants of each group also completed a Differential-Outcome Effect (DOE) task followed by a Slips-of-Action Task, designed to assess the balance of goal-directed and habitual behavioural control. Adolescent OCD patients showed a significant learning and memory impairment. Compared with healthy comparison subjects, they made more errors on PRM and PAL and in the first stages of IED involving discrimination and reversal learning. Patients were also slower to learn about contingencies in the DOE task and were less sensitive to outcome devaluation, suggesting an impairment in goal-directed control. This study advances the characterization of juvenile OCD. Patients demonstrated impairments in all learning and memory tasks. We also provide the first experimental evidence of impaired goal-directed control and lack of cognitive plasticity early in the development of OCD. The extent to which the impairments in these cognitive domains impact academic performance and symptom development warrants further investigation.

77 FR 15113 - Center for Scientific Review; Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-14

... Emphasis Panel; Member Conflict: Integrative Neuroscience. Date: March 28, 2012. Time: 1 p.m. to 3 p.m... Emphasis Panel; Member Conflict: Biobehavioral Regulation, Learning and Ethology. Date: April 4, 2012. Time...

SOCAP: Lessons learned in applying SIPE-2 to the military operations crisis action planning domain

NASA Technical Reports Server (NTRS)

Desimone, Roberto

1992-01-01

This report describes work funded under the DARPA Planning and Scheduling Initiative that led to the development of SOCAP (System for Operations Crisis Action Planning). In particular, it describes lessons learned in applying SIPE-2, the underlying AI planning technology within SOCAP, to the domain of military operations deliberate and crisis action planning. SOCAP was demonstrated at the U.S. Central Command and at the Pentagon in early 1992. A more detailed report about the lessons learned is currently being prepared. This report was presented during one of the panel discussions on 'The Relevance of Scheduling to AI Planning Systems.'

Extending the limits of complex learning in organic amnesia: computer training in a vocational domain.

PubMed

Glisky, E L; Schacter, D L

1989-01-01

This study explored the limits of learning that could be achieved by an amnesic patient in a complex real-world domain. Using a cuing procedure known as the method of vanishing cues, a severely amnesic encephalitic patient was taught over 250 discrete pieces of new information concerning the rules and procedures for performing a task involving data entry into a computer. Subsequently, she was able to use this acquired knowledge to perform the task accurately and efficiently in the workplace. These results suggest that amnesic patients' preserved learning abilities can be extended well beyond what has been reported previously.

Student Learning Approaches in the UAE: The Case for the Achieving Domain

ERIC Educational Resources Information Center

McLaughlin, James; Durrant, Philip

2017-01-01

The deep versus surface learning approach dichotomy has dominated recent research in student learning approach dimensions. However, the achievement dimension may differ in importance in non-Western and vocational tertiary settings. The aim was to assess how Emirati tertiary students could be characterized in terms of their learning approaches. The…

Exploring Students' Language Awareness through Intercultural Communication in Computer-Supported Collaborative Learning

ERIC Educational Resources Information Center

Yang, Yu-Fen

2013-01-01

Students seldom think about language unless they are instructed to do so or are made to do so during learning activities. To arouse students' awareness while learning English for Specific Purposes (ESP), this study formed a computer-supported collaborative learning (CSCL) community to engage teachers and students from different domains and…

Can a Hypermedia Cooperative e-Learning Environment Stimulate Constructive Collaboration?

ERIC Educational Resources Information Center

Pragnell, Mary Victoria; Roselli, Teresa; Rossano, Veronica

2006-01-01

The growing use of the Internet in learning environments has led to new models being created addressing specific learning domains, as well as more general educational goals. In particular, in recent years considerable attention has been paid to collaborative learning supported by technology, because this mode can enhance peer interaction and group…

Examining the Interrelations among Knowledge, Interests, and Learning Strategies

ERIC Educational Resources Information Center

Shen, Bo; Chen, Ang

2006-01-01

Guided by the Model of Domain Learning (MDL), the study was designed to explore the extent of interrelations among prior knowledge, learning strategies, interests, physical engagement, and learning outcomes in a sixth-grade (N = 91) volleyball unit. Pearson product-moment correlations and a path analysis were conducted for the research purpose.…

Teachers as Designers of Collaborative Distance Learning.

ERIC Educational Resources Information Center

Spector, J. Michael

There is an obvious growth in the use of distributed and online learning environments. There is some evidence to believe that collaborative learning environments can be effective, especially when using advanced technology to support learning in and about complex domains. There is also an extensive body of research literature in the areas of…

Adding Learning to Knowledge-Based Systems: Taking the "Artificial" Out of AI

Treesearch

Daniel L. Schmoldt

1997-01-01

Both, knowledge-based systems (KBS) development and maintenance require time-consuming analysis of domain knowledge. Where example cases exist, KBS can be built, and later updated, by incorporating learning capabilities into their architecture. This applies to both supervised and unsupervised learning scenarios. In this paper, the important issues for learning systems-...

A Comparison of the Efficacy of Individual and Collaborative Music Learning in Ensemble Rehearsals

ERIC Educational Resources Information Center

Brandler, Brian J.; Peynircioglu, Zehra F.

2015-01-01

Collaboration is essential in learning ensemble music. It is unclear, however, whether an individual benefits more from collaborative or individual rehearsal in the initial stages of such learning. In nonmusical domains, the effect of collaboration has been mixed, sometimes enhancing and sometimes inhibiting an individual's learning process. In…

Creating Significant Learning Experiences in a Large Undergraduate Psychology Class: A Pilot Study

ERIC Educational Resources Information Center

Fallahi, Carolyn R.; LaMonaca, Frank H., Jr.

2009-01-01

The authors redesigned a Lifespan Development course using Fink's (2003) taxonomy of significant learning and measured changes across his six domains: Knowledge, Application, Integration, Human Dimension, Caring, and Learning How to Learn. Using case studies and group work, 151 undergraduates completed identical pre- and post-tests that measured…

Effectiveness of eLearning in Statistics: Pictures and Stories

ERIC Educational Resources Information Center

Blackburn, Greg

2015-01-01

The study investigates (1) the effectiveness of using eLearning-embedded stories and pictures in order to improve learning outcomes for students and (2) how universities can adopt innovative approaches to the creation of Problem-Based Learning (PBL) resources and embed them in educational technology for teaching domain-specific content, such as…

Learning by Creating and Exchanging Objects: The SCY Experience

ERIC Educational Resources Information Center

De Jong, Ton; Van Joolingen, Wouter R.; Giemza, Adam; Girault, Isabelle; Hoppe, Ulrich; Kindermann, Jorg; Kluge, Anders; Lazonder, Ard W.; Vold, Vibeke; Weinberger, Armin; Weinbrenner, Stefan; Wichmann, Astrid; Anjewierden, Anjo; Bodin, Marjolaine; Bollen, Lars; D'Ham, Cedric; Dolonen, Jan; Engler, Jan; Geraedts, Caspar; Grosskreutz, Henrik; Hovardas, Tasos; Julien, Rachel; Lechner, Judith; Ludvigsen, Sten; Matteman, Yuri; Meistadt, Oyvind; Naess, Bjorge; Ney, Muriel; Pedaste, Margus; Perritano, Anthony; Rinket, Marieke; Von Schlanbusch, Henrik; Sarapuu, Tago; Schulz, Florian; Sikken, Jakob; Slotta, Jim; Toussaint, Jeremy; Verkade, Alex; Wajeman, Claire; Wasson, Barbara; Zacharia, Zacharias C.; Van Der Zanden, Martine

2010-01-01

Science Created by You (SCY) is a project on learning in science and technology domains. SCY uses a pedagogical approach that centres around products, called "emerging learning objects" (ELOs) that are created by students. Students work individually and collaboratively in SCY-Lab (the general SCY learning environment) on "missions" that are guided…

Examining Emotions in English Language Learning Classes: A Case of EFL Emotions

ERIC Educational Resources Information Center

Pishghadam, Reza; Zabetipour, Mohammad; Aminzadeh, Afrooz

2016-01-01

Emotions play a significant role in learning in general, and foreign language learning in particular. Although with the rise of humanistic approaches, enough attention has been given to the affective domain in language learning, the emotions English as a foreign language (EFL) learners experience regarding English language skills in listening,…

A Model for Discussing the Quality of Technology-Enhanced Learning in Blended Learning Programmes

ERIC Educational Resources Information Center

Casanova, Diogo; Moreira, António

2017-01-01

This paper presents a comprehensive model for supporting informed and critical discussions concerning the quality of Technology-Enhanced Learning in Blended Learning programmes. The model aims to support discussions around domains such as how institutions are prepared, the participants' background and expectations, the course design, and the…

Emotion in Organizational Learning-Implications for HRD

ERIC Educational Resources Information Center

Turnbull, Sharon

2004-01-01

In this article I draw attention to the under-researched domain of emotion in the study of organizational learning and its implications for HRD. The paper identifies four aspects of organization learning in which an emotional dimension is evident. These are: Emotion as a learned response, Emotion as codified meaning, Emotion as affective component…

The cost of concreteness: the effect of nonessential information on analogical transfer.

PubMed

Kaminski, Jennifer A; Sloutsky, Vladimir M; Heckler, Andrew F

2013-03-01

Most theories of analogical transfer focus on similarities between the learning and transfer domains, where transfer is more likely between domains that share common surface features, similar elements, or common interpretations of structure. We suggest that characteristics of the learning instantiation alone can give rise to different levels of transfer. We propose that concreteness of the learning instantiation can hinder analogical transfer of well-defined structured concepts, such as mathematical concepts. We operationalize the term concreteness as the amount of information communicated through a specific instantiation of a concept. The 5 reported experiments with undergraduate students tested the hypothesis by presenting participants with the concept of a commutative mathematical group of order 3. The experiments varied the level of concreteness of the training instantiation and measured transfer of learning to a new instantiation. The results support the hypothesis, demonstrating better transfer from more generic instantiations (i.e., ones that communicate minimal extraneous information) than from more concrete instantiations. Specifically, concreteness was found to create an obstacle to successful structural alignment across domains, whereas generic instantiations led to spontaneous structural alignment. These findings have important implications for the theory of learning and transfer and practical implications for the design of educational material. Although some concreteness may activate prior knowledge and perhaps offer a leg up in the learning process, this benefit may come at the cost of transfer.

Medical laboratory science and nursing students' perception of academic learning environment in a Philippine university using Dundee Ready Educational Environment Measure (DREEM).

PubMed

Barcelo, Jonathan M

2016-01-01

This study aimed to compare the perception of the academic learning environment between medical laboratory science students and nursing students at Saint Louis University, Baguio City, Philippines. A cross-sectional survey research design was used to measure the perceptions of the participants. A total of 341 students from the Department of Medical Laboratory Science, School of Natural Sciences, and the School of Nursing answered the Dundee Ready Education Environment Measure (DREEM) instrument from April to May 2016. Responses were compared according to course of study, gender, and year level. The total mean DREEM scores of the medical laboratory science students and nursing students did not differ significantly when grouped according to course of study, gender, or year level. Medical laboratory science students had significantly lower mean scores in the sub-domains 'perception of learning' and 'perception of teaching.' Male medical laboratory science students had significantly lower mean scores in the sub-domain 'perception of learning' among second year students. Medical laboratory science students had significantly lower mean scores in the sub-domain 'perception of learning.' Nursing students identified 7 problem areas, most of which were related to their instructors. Medical laboratory science and nursing students viewed their academic learning environment as 'more positive than negative.' However, the relationship of the nursing instructors to their students needs improvement.

Addiction History Associates with the Propensity to Form Habits.

PubMed

McKim, Theresa H; Bauer, Daniel J; Boettiger, Charlotte A

2016-07-01

Learned habitual responses to environmental stimuli allow efficient interaction with the environment, freeing cognitive resources for more demanding tasks. However, when the outcome of such actions is no longer a desired goal, established stimulus-response (S-R) associations or habits must be overcome. Among people with substance use disorders (SUDs), difficulty in overcoming habitual responses to stimuli associated with their addiction in favor of new, goal-directed behaviors contributes to relapse. Animal models of habit learning demonstrate that chronic self-administration of drugs of abuse promotes habitual responding beyond the domain of compulsive drug seeking. However, whether a similar propensity toward domain-general habitual responding occurs in humans with SUDs has remained unclear. To address this question, we used a visuomotor S-R learning and relearning task, the Hidden Association between Images Task, which employs abstract visual stimuli and manual responses. This task allows us to measure new S-R association learning and well-learned S-R association execution and includes a response contingency change manipulation to quantify the degree to which responding is habit-based, rather than goal-directed. We find that people with SUDs learn new S-R associations as well as healthy control participants do. Moreover, people with an SUD history slightly outperform controls in S-R execution. In contrast, people with SUDs are specifically impaired in overcoming well-learned S-R associations; those with SUDs make a significantly greater proportion of perseverative errors during well-learned S-R replacement, indicating the more habitual nature of their responses. Thus, with equivalent training and practice, people with SUDs appear to show enhanced domain-general habit formation.

Toward Automating HIV Identification: Machine Learning for Rapid Identification of HIV-Related Social Media Data.

PubMed

Young, Sean D; Yu, Wenchao; Wang, Wei

2017-02-01

"Social big data" from technologies such as social media, wearable devices, and online searches continue to grow and can be used as tools for HIV research. Although researchers can uncover patterns and insights associated with HIV trends and transmission, the review process is time consuming and resource intensive. Machine learning methods derived from computer science might be used to assist HIV domain experts by learning how to rapidly and accurately identify patterns associated with HIV from a large set of social data. Using an existing social media data set that was associated with HIV and coded by an HIV domain expert, we tested whether 4 commonly used machine learning methods could learn the patterns associated with HIV risk behavior. We used the 10-fold cross-validation method to examine the speed and accuracy of these models in applying that knowledge to detect HIV content in social media data. Logistic regression and random forest resulted in the highest accuracy in detecting HIV-related social data (85.3%), whereas the Ridge Regression Classifier resulted in the lowest accuracy. Logistic regression yielded the fastest processing time (16.98 seconds). Machine learning can enable social big data to become a new and important tool in HIV research, helping to create a new field of "digital HIV epidemiology." If a domain expert can identify patterns in social data associated with HIV risk or HIV transmission, machine learning models could quickly and accurately learn those associations and identify potential HIV patterns in large social data sets.

International health IT benchmarking: learning from cross-country comparisons.

PubMed

Zelmer, Jennifer; Ronchi, Elettra; Hyppönen, Hannele; Lupiáñez-Villanueva, Francisco; Codagnone, Cristiano; Nøhr, Christian; Huebner, Ursula; Fazzalari, Anne; Adler-Milstein, Julia

2017-03-01

To pilot benchmark measures of health information and communication technology (ICT) availability and use to facilitate cross-country learning. A prior Organization for Economic Cooperation and Development-led effort involving 30 countries selected and defined functionality-based measures for availability and use of electronic health records, health information exchange, personal health records, and telehealth. In this pilot, an Organization for Economic Cooperation and Development Working Group compiled results for 38 countries for a subset of measures with broad coverage using new and/or adapted country-specific or multinational surveys and other sources from 2012 to 2015. We also synthesized country learnings to inform future benchmarking. While electronic records are widely used to store and manage patient information at the point of care-all but 2 pilot countries reported use by at least half of primary care physicians; many had rates above 75%-patient information exchange across organizations/settings is less common. Large variations in the availability and use of telehealth and personal health records also exist. Pilot participation demonstrated interest in cross-national benchmarking. Using the most comparable measures available to date, it showed substantial diversity in health ICT availability and use in all domains. The project also identified methodological considerations (e.g., structural and health systems issues that can affect measurement) important for future comparisons. While health policies and priorities differ, many nations aim to increase access, quality, and/or efficiency of care through effective ICT use. By identifying variations and describing key contextual factors, benchmarking offers the potential to facilitate cross-national learning and accelerate the progress of individual countries. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Self-regulated learning of basic arithmetic skills: a longitudinal study.

PubMed

Throndsen, Inger

2011-12-01

Several studies have examined young primary school children's use of strategies when solving simple addition and subtraction problems. Most of these studies have investigated students' strategy use as if they were isolated processes. To date, we have little knowledge about how math strategies in young students are related to other important aspects in self-regulated learning. The main purpose of this study was to examine relations between young primary school children's basic mathematical skills and their use of math strategies, their metacognitive competence and motivational beliefs, and to investigate how students with basic mathematics skills at various levels differ in respect to the different self-regulation components. The participants were comprised of 27 Year 2 students, all from the same class. The data were collected in three stages (autumn Year 2, spring Year 2, and autumn Year 3). The children's arithmetic skills were measured by age relevant tests, while strategy use, metacognitive competence, and motivational beliefs were assessed through individual interviews. The participants were divided into three performance groups; very good students, good students, and not-so-good students. Analyses revealed that young primary school children at different levels of basic mathematics skill may differ in several important aspects of self-regulated learning. Analyses revealed that a good performance in addition and subtraction was related not only to the children's use of advanced mathematics strategies, but also to domain-specific metacognitive competence, ability attribution for success, effort attribution for failure, and high perceived self-efficacy when using specific strategies. The results indicate that instructional efforts to facilitate self-regulated learning of basic arithmetic skills should address cognitive, metacognitive, and motivational aspects of self-regulation. This is particularly important for low-performing students. ©2010 The British Psychological Society.

How Do We Go about "Knowing" the Culture of Our School?

ERIC Educational Resources Information Center

Achilles, C. M.

Research on learning styles has shown that students learn better when teachers plan class learning activities to fit students' learning styles. This paper describes three "ways of knowing" and discusses the role they play in "knowing the culture" of a school. The first part relates ways of knowing to the usual three domains of learning--cognitive,…

Using Learning Trajectories to Enhance Formative Assessment

ERIC Educational Resources Information Center

Ebby, Caroline B.; Petit, Marjorie

2017-01-01

A learning trajectory describes the progression of student thinking and strategies over time in terms of sophistication of both conceptual understanding and procedural fluency. Currently, learning trajectories exist in the research literature for many mathematical domains, including counting, addition and subtraction, multiplicative thinking,…

BIBLIOGRAPHY ON LEARNING PROCESS. SUPPLEMENT II.

ERIC Educational Resources Information Center

Harvard Univ., Cambridge, MA. Graduate School of Education.

THIS SUPPLEMENTARY BIBLIOGRAPHY LISTS MATERIALS ON VARIOUS FACETS OF HUMAN LEARNING. APPROXIMATELY 60 UNANNOTATED REFERENCES ARE PROVIDED FOR DOCUMENTS DATING FROM 1954 TO 1966. JOURNAL ARTICLES, BOOKS, RESEARCH REPORTS, AND CONFERENCE PAPERS ARE LISTED. SOME SUBJECT AREAS INCLUDED ARE (1) LEARNING PARAMETERS AND ABILITY, (2) RETENTION AND…

78 FR 38915 - Notice of Available Funding and Grant Application Deadlines

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-28

... Learning and Telemedicine (DLT) Grant Program for the Fiscal Year (FY) 2013 competition. DATES: You may... Federal Agency: Rural Utilities Service (RUS). Funding Opportunity Title: Distance Learning and... financial assistance to encourage and improve telemedicine services and distance learning services in rural...

The Dating Game: An Exercise Illustrating the Concepts of Homogamy, Heterogamy, Hyperogamy, and Hypogamy.

ERIC Educational Resources Information Center

O'Brien, Eileen; Foley, Lara

1999-01-01

Describes the "Dating Game," an exercise for use in marriage and family courses that enables students to learn about the theories of mate selection by simulating random mating. States that the dating game helps make mate selection concepts relevant to the students' lives. Discusses the students' reaction to the exercise. (CMK)

Addiction history associates with the propensity to form habits

PubMed Central

McKim, Theresa H.; Bauer, Daniel J.; Boettiger, Charlotte A.

2016-01-01

Learned habitual responses to environmental stimuli allow efficient interaction with the environment, freeing cognitive resources for more demanding tasks. However, when the outcome of such actions is no longer a desired goal, established stimulus-response (S-R) associations, or habits, must be overcome. Among people with substance use disorders (SUDs), difficulty in overcoming habitual responses to stimuli associated with their addiction in favor of new, goal-directed behaviors, contributes to relapse. Animal models of habit learning demonstrate that chronic self-administration of drugs of abuse promotes habitual responding beyond the domain of compulsive drug seeking. However, whether a similar propensity toward domain-general habitual responding occurs in humans with SUDs has remained unclear. To address this question, we used a visuomotor S-R learning and re-learning task, the Hidden Association Between Images Task (HABIT), which employs abstract visual stimuli and manual responses. This task allows us to measure new S-R association learning, well-learned S-R association execution, and includes a response contingency change manipulation to quantify the degree to which responding is habit-based, rather than goal-directed. We find that people with SUDs learn new S-R associations as well as healthy control subjects do. Moreover, people with an SUD history slightly outperform controls in S-R execution. In contrast, people with SUDs are specifically impaired in overcoming well-learned S-R associations; those with SUDs make a significantly greater proportion of perseverative errors during well-learned S-R replacement, indicating the more habitual nature of their responses. Thus, with equivalent training and practice, people with SUDs appear to show enhanced domain-general habit formation. PMID:26967944

Quality management of eLearning for medical education: current situation and outlook

PubMed Central

Abrusch, Jasmin; Marienhagen, Jörg; Böckers, Anja; Gerhardt-Szép, Susanne

2015-01-01

Introduction: In 2008, the German Council of Science had advised universities to establish a quality management system (QMS) that conforms to international standards. The system was to be implemented within 5 years, i.e., until 2014 at the latest. The aim of the present study was to determine whether a QMS suitable for electronic learning (eLearning) domain of medical education to be used across Germany has meanwhile been identified. Methods: We approached all medical universities in Germany (n=35), using an anonymous questionnaire (8 domains, 50 items). Results: Our results (response rate 46.3%) indicated very reluctant application of QMS in eLearning and a major information deficit at the various institutions. Conclusions: Authors conclude that under the limitations of this study there seems to be a considerable need to improve the current knowledge on QMS for eLearning, and that clear guidelines and standards for their implementation should be further defined. PMID:26038685

Quality management of eLearning for medical education: current situation and outlook.

PubMed

Abrusch, Jasmin; Marienhagen, Jörg; Böckers, Anja; Gerhardt-Szép, Susanne

2015-01-01

In 2008, the German Council of Science had advised universities to establish a quality management system (QMS) that conforms to international standards. The system was to be implemented within 5 years, i.e., until 2014 at the latest. The aim of the present study was to determine whether a QMS suitable for electronic learning (eLearning) domain of medical education to be used across Germany has meanwhile been identified. We approached all medical universities in Germany (n=35), using an anonymous questionnaire (8 domains, 50 items). Our results (response rate 46.3%) indicated very reluctant application of QMS in eLearning and a major information deficit at the various institutions. Authors conclude that under the limitations of this study there seems to be a considerable need to improve the current knowledge on QMS for eLearning, and that clear guidelines and standards for their implementation should be further defined.

Learning through ferroelectric domain dynamics in solid-state synapses

NASA Astrophysics Data System (ADS)

Boyn, Sören; Grollier, Julie; Lecerf, Gwendal; Xu, Bin; Locatelli, Nicolas; Fusil, Stéphane; Girod, Stéphanie; Carrétéro, Cécile; Garcia, Karin; Xavier, Stéphane; Tomas, Jean; Bellaiche, Laurent; Bibes, Manuel; Barthélémy, Agnès; Saïghi, Sylvain; Garcia, Vincent

2017-04-01

In the brain, learning is achieved through the ability of synapses to reconfigure the strength by which they connect neurons (synaptic plasticity). In promising solid-state synapses called memristors, conductance can be finely tuned by voltage pulses and set to evolve according to a biological learning rule called spike-timing-dependent plasticity (STDP). Future neuromorphic architectures will comprise billions of such nanosynapses, which require a clear understanding of the physical mechanisms responsible for plasticity. Here we report on synapses based on ferroelectric tunnel junctions and show that STDP can be harnessed from inhomogeneous polarization switching. Through combined scanning probe imaging, electrical transport and atomic-scale molecular dynamics, we demonstrate that conductance variations can be modelled by the nucleation-dominated reversal of domains. Based on this physical model, our simulations show that arrays of ferroelectric nanosynapses can autonomously learn to recognize patterns in a predictable way, opening the path towards unsupervised learning in spiking neural networks.

The history of the CATH structural classification of protein domains.

PubMed

Sillitoe, Ian; Dawson, Natalie; Thornton, Janet; Orengo, Christine

2015-12-01

This article presents a historical review of the protein structure classification database CATH. Together with the SCOP database, CATH remains comprehensive and reasonably up-to-date with the now more than 100,000 protein structures in the PDB. We review the expansion of the CATH and SCOP resources to capture predicted domain structures in the genome sequence data and to provide information on the likely functions of proteins mediated by their constituent domains. The establishment of comprehensive function annotation resources has also meant that domain families can be functionally annotated allowing insights into functional divergence and evolution within protein families. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

48 CFR 871.207 - Payment of tuition or fees.

Code of Federal Regulations, 2010 CFR

2010-10-01

... the following: (i) An institution of higher learning that uses a standard unit of credit recognized by... period of actual enrollment and is subject to the following: (1) The effective date is the date of the...

48 CFR 871.207 - Payment of tuition or fees.

Code of Federal Regulations, 2011 CFR

2011-10-01

... the following: (i) An institution of higher learning that uses a standard unit of credit recognized by... period of actual enrollment and is subject to the following: (1) The effective date is the date of the...

48 CFR 871.207 - Payment of tuition or fees.

Code of Federal Regulations, 2012 CFR

2012-10-01

... the following: (i) An institution of higher learning that uses a standard unit of credit recognized by... period of actual enrollment and is subject to the following: (1) The effective date is the date of the...

48 CFR 871.207 - Payment of tuition or fees.

Code of Federal Regulations, 2014 CFR

2014-10-01

... the following: (i) An institution of higher learning that uses a standard unit of credit recognized by... period of actual enrollment and is subject to the following: (1) The effective date is the date of the...

48 CFR 871.207 - Payment of tuition or fees.

Code of Federal Regulations, 2013 CFR

2013-10-01

... the following: (i) An institution of higher learning that uses a standard unit of credit recognized by... period of actual enrollment and is subject to the following: (1) The effective date is the date of the...

Defining the Relationship of Student Achievement Between STEM Subjects Through Canonical Correlation Analysis of 2011 Trends in International Mathematics and Science Study (TIMSS) Data

NASA Astrophysics Data System (ADS)

O'Neal, Melissa Jean

Canonical correlation analysis was used to analyze data from Trends in International Mathematics and Science Study (TIMSS) 2011 achievement databases encompassing information from fourth/eighth grades. Student achievement in life science/biology was correlated with achievement in mathematics and other sciences across three analytical areas: mathematics and science student performance, achievement in cognitive domains, and achievement in content domains. Strong correlations between student achievement in life science/biology with achievement in mathematics and overall science occurred for both high- and low-performing education systems. Hence, partial emphases on the inter-subject connections did not always lead to a better student learning outcome in STEM education. In addition, student achievement in life science/biology was positively correlated with achievement in mathematics and science cognitive domains; these patterns held true for correlations of life science/biology with mathematics as well as other sciences. The importance of linking student learning experiences between and within STEM domains to support high performance on TIMSS assessments was indicated by correlations of moderate strength (57 TIMSS assessments was indicated by correlations of moderate strength (57 < r < 85) stronger correlations (73 < r < 97) between life science/biology and other science domains. Results demonstrated the foundational nature of STEM knowledge at the fourth grade level, and established the importance of strong interconnections among life science/biology, mathematics, and other sciences. At the eighth grade level, students who built increasing levels of cognitive complexity upon firm foundations were prepared for successful learning throughout their educational careers. The results from this investigation promote a holistic design of school learning opportunities to improve student achievement in life science/biology and other science, technology, engineering, and mathematics (STEM) subjects at the elementary and middle school levels. While the curriculum can vary from combined STEM subjects to separated mathematics or science courses, both professional learning communities (PLC) for teachers and problem-based learning (PBL) for learners can be strengthened through new knowledge construction beyond the traditional boundaries of each subject. It is the knowledge transfer across subjects that breaks barriers of future STEM discoveries to improve STEM education outcomes.

Affordances and Limitations of Learning Analytics for Computer-Assisted Language Learning: A Case Study of the VITAL Project

ERIC Educational Resources Information Center

Gelan, Anouk; Fastré, Greet; Verjans, Martine; Martin, Niels; Janssenswillen, Gert; Creemers, Mathijs; Lieben, Jonas; Depaire, Benoît; Thomas, Michael

2018-01-01

Learning analytics (LA) has emerged as a field that offers promising new ways to prevent drop-out and aid retention. However, other research suggests that large datasets of learner activity can be used to understand online learning behaviour and improve pedagogy. While the use of LA in language learning has received little attention to date,…

Weblogs for English Language Learning: Students' Perceptions

ERIC Educational Resources Information Center

Wan, Juida; Tan, Bee Hoon

2011-01-01

The digital explosion of information on the Internet has resulted in a need for a new and up-to-date way for Digital Natives to learn English. Educators have reported numerous benefits of using weblogs in English language learning. This article presents a small scale study on the use of weblogs for English language learning at tertiary level in…

How Cognitive Styles Affect the Learning Behaviors of Online Problem-Solving Based Discussion Activity: A Lag Sequential Analysis

ERIC Educational Resources Information Center

Wu, Sheng-Yi; Hou, Huei-Tse

2015-01-01

Cognitive styles play an important role in influencing the learning process, but to date no relevant study has been conducted using lag sequential analysis to assess knowledge construction learning patterns based on different cognitive styles in computer-supported collaborative learning activities in online collaborative discussions. This study…

The Effect of Blended Learning on Math and Reading Achievement in a Charter School Context

ERIC Educational Resources Information Center

Chaney, Terry Andrew

2017-01-01

In spite of its growing popularity, researchers have focused little attention on the effectiveness of combining traditional classroom instruction and online learning, a practice generally referred to as blended learning. The modest research on blended learning to date has tended to focus on higher education, leaving a significant gap in the…

Unlocking Learning Using Tony Ryan's "Thinker's Keys"

ERIC Educational Resources Information Center

Robinson, Linda

2017-01-01

The learning of science keeps evolving, just like the subject of science itself. With this in mind, teachers know the importance of keeping up to date and researching different ways of providing a rich learning experience for children. Teachers are developing not only children's learning, but how they progress as learners. This is where Tony…

Back to Learning: How Research-Based Classroom Instruction Can Make the Impossible Possible

ERIC Educational Resources Information Center

Parsons, Les

2012-01-01

Based on the most up-to-date research, "Back to Learning" presents straightforward analysis and practical guidance on confronting bullying, taming the digital universe, and changing the troublesome trend in students' entitled attitudes toward learning and grades. "Back to Learning" gives teachers the background they need to: (1) understand how the…

Optical Imaging of the Nearshore

DTIC Science & Technology

2010-09-30

understand the dynamics of the nearshore system that we measure. APPROACH We exploit a number of approaches in our work. Our observational...resolution, time domain data of optical radiance at a number of focus research sites. Recently, we have collaborated with Dr. Merrick Haller of OSU to...not display a currently valid OMB control number . 1. REPORT DATE 2011 2. REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE Optical

Adventure-Based Learning across Domains.

ERIC Educational Resources Information Center

Garside, Colleen

With "adventure-based" learning, instructors present activities in a way that allows the group to develop its own abilities, with guidance from the instructor when appropriate. Adventure-based learning activities (which emphasize the importance of play) lend themselves to inclusion in the basic speech communication course, particularly…

The One School Roomhouse: An Information and Learning Approach to Curriculum Integration.

ERIC Educational Resources Information Center

McKinney, Earl H., Jr.; Yoos, Charles J., II

1998-01-01

Three undergraduate courses--marketing, strategy, and management information systems--were brought together using a metalanguage of learning common to each domain. The intent was to encourage students to appreciate complexity, take responsibility for learning, work in teams, and communicate effectively. (SK)

Extending human potential in a technical learning environment

NASA Astrophysics Data System (ADS)

Fielden, Kay A.

This thesis is a report of a participatory inquiry process looking at enhancing the learning process in a technical academic field in high education by utilising tools and techniques which go beyond the rational/logical, intellectual domain in a functional, objective world. By empathising with, nurturing and sustaining the whole person, and taking account of past patterning as well as future visions including technological advances to augment human awareness, the scene is set for depth learning. Depth learning in a tertiary environment can only happen as a result of the dynamic that exists between the dominant, logical/rational, intellectual paradigm and the experiential extension of the boundaries surrounding this domain. Any experiences which suppress the full, holistic expression of our being alienate us from the fullness of the expression and hence from depth learning. Depth learning is indicated by intrinsic motivation, which is more likely to occur in a trusting and supporting environment. The research took place within a systemic intellectual framework, where emergence is the prime characteristic used to evaluate results.

Primetime for Learning Genes.

PubMed

Keifer, Joyce

2017-02-11

Learning genes in mature neurons are uniquely suited to respond rapidly to specific environmental stimuli. Expression of individual learning genes, therefore, requires regulatory mechanisms that have the flexibility to respond with transcriptional activation or repression to select appropriate physiological and behavioral responses. Among the mechanisms that equip genes to respond adaptively are bivalent domains. These are specific histone modifications localized to gene promoters that are characteristic of both gene activation and repression, and have been studied primarily for developmental genes in embryonic stem cells. In this review, studies of the epigenetic regulation of learning genes in neurons, particularly the brain-derived neurotrophic factor gene ( BDNF ), by methylation/demethylation and chromatin modifications in the context of learning and memory will be highlighted. Because of the unique function of learning genes in the mature brain, it is proposed that bivalent domains are a characteristic feature of the chromatin landscape surrounding their promoters. This allows them to be "poised" for rapid response to activate or repress gene expression depending on environmental stimuli.

Cognitive ability predicts motor learning on a virtual reality game in patients with TBI.

PubMed

O'Neil, Rochelle L; Skeel, Reid L; Ustinova, Ksenia I

2013-01-01

Virtual reality games and simulations have been utilized successfully for motor rehabilitation of individuals with traumatic brain injury (TBI). Little is known, however, how TBI-related cognitive decline affects learning of motor tasks in virtual environments. To fill this gap, we examined learning within a virtual reality game involving various reaching motions in 14 patients with TBI and 15 healthy individuals with different cognitive abilities. All participants practiced ten 90-second gaming trials to assess various aspects of motor learning. Cognitive abilities were assessed with a battery of tests including measures of memory, executive functioning, and visuospatial ability. Overall, participants with TBI showed both reduced performance and a slower learning rate in the virtual reality game compared to healthy individuals. Numerous correlations between overall performance and several of the cognitive ability domains were revealed for both the patient and control groups, with the best predictor being overall cognitive ability. The results may provide a starting point for rehabilitation programs regarding which cognitive domains interact with motor learning.

Military Vision Research Program

DTIC Science & Technology

2011-02-01

present in vitreous appears to associate with the extracellular domain of PDGFRα • Galectin 3 was identified by mass spec as one of the vitreal...proteins that bound to the extracellular domain of PDGFRα • Recombinant galectin 3 did not prevent PDGF from activating PDGFRα, and is therefore not...February 28, 2011 2. REPORT TYPE Final 3 . DATES COVERED (From - To) 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER W81XWH-09-2-0091

Historical Time-Domain: Data Archives, Processing, and Distribution

NASA Astrophysics Data System (ADS)

Grindlay, Jonathan E.; Griffin, R. Elizabeth

2012-04-01

The workshop on Historical Time-Domain Astronomy (TDA) was attended by a near-capacity gathering of ~30 people. From information provided in turn by those present, an up-to-date overview was created of available plate archives, progress in their digitization, the extent of actual processing of those data, and plans for data distribution. Several recommendations were made for prioritising the processing and distribution of historical TDA data.

The Role and Potential Dangers of Visualisation When Learning about Sub-Microscopic Explanations in Chemistry Education

ERIC Educational Resources Information Center

Eilks, Ingo; Witteck, Torsten; Pietzner, Verena

2012-01-01

The core of theory-driven chemistry education consists of the constant shift between the different representational domains of chemical thinking: the macroscopic, the sub-microscopic, and the symbolic domains. Because the sub-microscopic domain can neither be seen nor directly visualised, it requires specific forms of visualisation, i.e. pictures…

Domain Approach: An Alternative Approach in Moral Education

ERIC Educational Resources Information Center

Vengadasalam, Chander; Mamat, Wan Hasmah Wan; Mail, Fauziah; Sudramanian, Munimah

2014-01-01

This paper discusses the use of the domain approach in moral education in an upper secondary school in Malaysia. Moral Education needs a creative and an innovative approach. Therefore, a few forms of approaches are used in the teaching-learning of Moral Education. This research describes the use of domain approach which comprises the moral domain…

Discriminative Transfer Subspace Learning via Low-Rank and Sparse Representation.

PubMed

Xu, Yong; Fang, Xiaozhao; Wu, Jian; Li, Xuelong; Zhang, David

2016-02-01

In this paper, we address the problem of unsupervised domain transfer learning in which no labels are available in the target domain. We use a transformation matrix to transfer both the source and target data to a common subspace, where each target sample can be represented by a combination of source samples such that the samples from different domains can be well interlaced. In this way, the discrepancy of the source and target domains is reduced. By imposing joint low-rank and sparse constraints on the reconstruction coefficient matrix, the global and local structures of data can be preserved. To enlarge the margins between different classes as much as possible and provide more freedom to diminish the discrepancy, a flexible linear classifier (projection) is obtained by learning a non-negative label relaxation matrix that allows the strict binary label matrix to relax into a slack variable matrix. Our method can avoid a potentially negative transfer by using a sparse matrix to model the noise and, thus, is more robust to different types of noise. We formulate our problem as a constrained low-rankness and sparsity minimization problem and solve it by the inexact augmented Lagrange multiplier method. Extensive experiments on various visual domain adaptation tasks show the superiority of the proposed method over the state-of-the art methods. The MATLAB code of our method will be publicly available at http://www.yongxu.org/lunwen.html.

Approaches to Machine Learning.

DTIC Science & Technology

1984-02-16

The field of machine learning strives to develop methods and techniques to automatic the acquisition of new information, new skills, and new ways of organizing existing information. In this article, we review the major approaches to machine learning in symbolic domains, covering the tasks of learning concepts from examples, learning search methods, conceptual clustering, and language acquisition. We illustrate each of the basic approaches with paradigmatic examples. (Author)

Designing and Integrating Purposeful Learning in Game Play: A Systematic Review

ERIC Educational Resources Information Center

Ke, Fengfeng

2016-01-01

Via a systematic review of the literature on learning games, this article presents a systematic discussion on the design of intrinsic integration of domain-specific learning in game mechanics and game world design. A total of 69 articles ultimately met the inclusion criteria and were coded for the literature synthesis. Exemplary learning games…

Using Multilingual Analytics to Explore the Usage of a Learning Portal in Developing Countries

ERIC Educational Resources Information Center

Protonotarios, Vassilis; Stoitsis, Giannis; Kastrantas, Kostas; Sanchez-Alonso, Salvador

2013-01-01

Learning analytics is a domain that has been constantly evolving throughout recent years due to the acknowledgement of its importance by those using intelligent data, learner-produced data, and analysis models to discover information and social connections for predicting and advising people's learning [1]. Learning analytics may be applied in a…

Higher Education Student Learning beyond the Classroom: Findings from a Community Music Service Learning Project in Rural South Africa

ERIC Educational Resources Information Center

Harrop-Allin, Susan

2017-01-01

Inspired by local arts community engagement initiatives and community music interventions internationally, Wits University (in Johannesburg, South Africa) developed a model of service learning that links the intentions, methodologies and purposes of these domains to promote student learning and benefit communities. This paper examines the quality…

Educational Application of Dialogue System To Support e-Learning.

ERIC Educational Resources Information Center

Kim, Youn-Gi; Lee, Chul-Hwan; Han, Sun-Gwan

This study is on the design and implementation of an educational dialogue system to support e-learning. The learning domain to apply the dialogue system used the subject of geometry. The knowledge in the dialogue-based system for learning geometry was created and represented by XML-based AIML. The implemented system in this study can understand…

Epistemic Trust and Education: Effects of Informant Reliability on Student Learning of Decimal Concepts

ERIC Educational Resources Information Center

Durkin, Kelley; Shafto, Patrick

2016-01-01

The epistemic trust literature emphasizes that children's evaluations of informants' trustworthiness affects learning, but there is no evidence that epistemic trust affects learning in academic domains. The current study investigated how reliability affects decimal learning. Fourth and fifth graders (N = 122; M[subscript age] = 10.1 years)…

Teaching and Learning in History: Effective and Reform-Based Practices for Students with Learning Disabilities

ERIC Educational Resources Information Center

De La Paz, Susan

2013-01-01

This article provides a review of effective and reform-based approaches to instruction that focus on teaching and learning of history for students with LD. Historical thinking goals, such as learning to think like a historian, to develop contextualized understandings, and to apply domain-specific approaches when reading and writing with primary…

Powerful Feelings: Exploring the Affective Domain of Informal and Arts-Based Learning

ERIC Educational Resources Information Center

Lawrence, Randee Lipson

2008-01-01

This article looks at the ways in which people learn informally through artistic expression such as dance, drama, poetry, music, literature, film, and all of the visual arts and how people access this learning through their emotions. The author begins with a look at the limitations of relying primarily on technical-rational learning processes.…

Impact of Cooperative Learning in Developing Students' Cognitive Abilities for Academic Achievement

ERIC Educational Resources Information Center

Hoorani, Bareerah Hafeez

2014-01-01

This study used an Action Research Method to investigate ways to improve the thinking and reasoning skills of grade eight science students in an under-resourced school in Karachi. The students' rote learning patterns were challenged using the schema provided by Blooms' taxonomy of learning domains. A cooperative learning environment was generated…

A THz Superconducting Imaging Array Developed for the DATE5 Telescope

NASA Astrophysics Data System (ADS)

Shi, Sheng-Cai; Zhang, Wen; Li, Jing; Miao, Wei; Lin, Zhen-Hui; Lou, Zheng; Yao, Qi-Jun

2016-08-01

Dome A in Antarctica, located at an altitude of 4093 m and with very low temperature in winter down to -83^{circ }C, is an exceptionally dry site. Measurements of the atmospheric transmission in the range of 0.75-15 THz by a Far-infrared/THz Fourier transform spectrometer (FTS) strongly suggest that Dome A is a unique site for ground-based THz observations, especially for the 200- and 350-micron windows. A 5-m THz telescope (DATE5) is therefore proposed for Chinese Antarctic Kunlun Observatory. We are currently developing a THz superconducting imaging array (TeSIA) for the DATE5. The TeSIA will be working at the 350-\\upmu m window, with a pixel number of 32 × 32 and a sensitivity (NEP) of ˜ 10^{-16} W/Hz^{0.5}. Ti transition-edge sensors with time-domain multiplexing and TiN microwave kinetic inductance detectors with frequency-domain multiplexing are both developed for the TeSIA. In this paper, detailed system designs and some measurement results will be presented.

Quality indicators for learner-centered postgraduate medical e-learning.

PubMed

de Leeuw, Robert A; Westerman, Michiel; Scheele, Fedde

2017-04-27

The objectives of this study were to identify the needs and expectations of learners and educational experts in postgraduate medical e-learning, and to contribute to the current literature. We performed four focus-group discussions with e-learning end-users (learners) and didactic experts. The participants were postgraduate learners with varying levels of experience, educational experts from a Dutch e-learning task group, and commercial experts from a Dutch e-learning company. Verbatim transcribed interview recordings were analyzed using King's template analysis. The initial template was created with reference to recent literature on postgraduate medical e-learning quality indicators. The transcripts were coded, after which the emerging differences in template interpretation were discussed until a consensus was reached within the team. The final template consisted of three domains of positive e-learning influencers (motivators, learning enhancers, and real-world translation) and three domains of negatively influential parameters (barriers, learning discouragers, and poor preparation). The interpretation of the final template showed three subjects which form the basis of e-learning, namely, Motivate, Learn and Apply. This study forms a basis for learning in general and could be applied to many educational instruments. Individual characteristics should be adapted to the target audience. Three subjects form the basis of, and six themes cover all items needed for, good (enough) postgraduate e-learning. Further research should be carried out with learners and real-world e-learning to validate this template.

Learning styles and academic achievement among undergraduate medical students in Thailand

PubMed Central

Jiraporncharoen, Wichuda; Angkurawaranon, Chaisiri; Chockjamsai, Manoch; Deesomchok, Athavudh; Euathrongchit, Juntima

2015-01-01

Purpose: This study aimed to explore the associations between learning styles and high academic achievement and to ascertain whether the factors associated with high academic achievement differed between preclinical and clinical students. Methods: A survey was conducted among undergraduate medical students in Chiang Mai University, Thailand. The Index of Learning Styles questionnaire was used to assess each student’s learning style across four domains. High academic achievement was defined as a grade point average of at least 3.0. Results: Of the 1,248 eligible medical students, 1,014 (81.3%) participated. Learning styles differed between the preclinical and clinical students in the active/reflective domain. A sequential learning style was associated with high academic achievement in both preclinical and clinical students. A reflective learning style was only associated with high academic achievement among preclinical students. Conclusion: The association between learning styles and academic achievement may have differed between preclinical and clinical students due to different learning content and teaching methods. Students should be encouraged to be flexible in their own learning styles in order to engage successfully with various and changing teaching methods across the curriculum. Instructors should be also encouraged to provide a variety of teaching materials and resources to suit different learning styles. PMID:26165948

A Pilot Study of Biomedical Text Comprehension using an Attention-Based Deep Neural Reader: Design and Experimental Analysis.

PubMed

Kim, Seongsoon; Park, Donghyeon; Choi, Yonghwa; Lee, Kyubum; Kim, Byounggun; Jeon, Minji; Kim, Jihye; Tan, Aik Choon; Kang, Jaewoo

2018-01-05

With the development of artificial intelligence (AI) technology centered on deep-learning, the computer has evolved to a point where it can read a given text and answer a question based on the context of the text. Such a specific task is known as the task of machine comprehension. Existing machine comprehension tasks mostly use datasets of general texts, such as news articles or elementary school-level storybooks. However, no attempt has been made to determine whether an up-to-date deep learning-based machine comprehension model can also process scientific literature containing expert-level knowledge, especially in the biomedical domain. This study aims to investigate whether a machine comprehension model can process biomedical articles as well as general texts. Since there is no dataset for the biomedical literature comprehension task, our work includes generating a large-scale question answering dataset using PubMed and manually evaluating the generated dataset. We present an attention-based deep neural model tailored to the biomedical domain. To further enhance the performance of our model, we used a pretrained word vector and biomedical entity type embedding. We also developed an ensemble method of combining the results of several independent models to reduce the variance of the answers from the models. The experimental results showed that our proposed deep neural network model outperformed the baseline model by more than 7% on the new dataset. We also evaluated human performance on the new dataset. The human evaluation result showed that our deep neural model outperformed humans in comprehension by 22% on average. In this work, we introduced a new task of machine comprehension in the biomedical domain using a deep neural model. Since there was no large-scale dataset for training deep neural models in the biomedical domain, we created the new cloze-style datasets Biomedical Knowledge Comprehension Title (BMKC_T) and Biomedical Knowledge Comprehension Last Sentence (BMKC_LS) (together referred to as BioMedical Knowledge Comprehension) using the PubMed corpus. The experimental results showed that the performance of our model is much higher than that of humans. We observed that our model performed consistently better regardless of the degree of difficulty of a text, whereas humans have difficulty when performing biomedical literature comprehension tasks that require expert level knowledge. ©Seongsoon Kim, Donghyeon Park, Yonghwa Choi, Kyubum Lee, Byounggun Kim, Minji Jeon, Jihye Kim, Aik Choon Tan, Jaewoo Kang. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 05.01.2018.

The cerebellum and visual perceptual learning: evidence from a motion extrapolation task.

PubMed

Deluca, Cristina; Golzar, Ashkan; Santandrea, Elisa; Lo Gerfo, Emanuele; Eštočinová, Jana; Moretto, Giuseppe; Fiaschi, Antonio; Panzeri, Marta; Mariotti, Caterina; Tinazzi, Michele; Chelazzi, Leonardo

2014-09-01

Visual perceptual learning is widely assumed to reflect plastic changes occurring along the cerebro-cortical visual pathways, including at the earliest stages of processing, though increasing evidence indicates that higher-level brain areas are also involved. Here we addressed the possibility that the cerebellum plays an important role in visual perceptual learning. Within the realm of motor control, the cerebellum supports learning of new skills and recalibration of motor commands when movement execution is consistently perturbed (adaptation). Growing evidence indicates that the cerebellum is also involved in cognition and mediates forms of cognitive learning. Therefore, the obvious question arises whether the cerebellum might play a similar role in learning and adaptation within the perceptual domain. We explored a possible deficit in visual perceptual learning (and adaptation) in patients with cerebellar damage using variants of a novel motion extrapolation, psychophysical paradigm. Compared to their age- and gender-matched controls, patients with focal damage to the posterior (but not the anterior) cerebellum showed strongly diminished learning, in terms of both rate and amount of improvement over time. Consistent with a double-dissociation pattern, patients with focal damage to the anterior cerebellum instead showed more severe clinical motor deficits, indicative of a distinct role of the anterior cerebellum in the motor domain. The collected evidence demonstrates that a pure form of slow-incremental visual perceptual learning is crucially dependent on the intact cerebellum, bearing the notion that the human cerebellum acts as a learning device for motor, cognitive and perceptual functions. We interpret the deficit in terms of an inability to fine-tune predictive models of the incoming flow of visual perceptual input over time. Moreover, our results suggest a strong dissociation between the role of different portions of the cerebellum in motor versus non-motor functions, with only the posterior lobe being responsible for learning in the perceptual domain. Copyright © 2014. Published by Elsevier Ltd.

Fluorescent-responsive synthetic C1b domains of protein kinase Cδ as reporters of specific high-affinity ligand binding.

PubMed

Ohashi, Nami; Nomura, Wataru; Narumi, Tetsuo; Lewin, Nancy E; Itotani, Kyoko; Blumberg, Peter M; Tamamura, Hirokazu

2011-01-19

Protein kinase C (PKC) is a critical cell signaling pathway involved in many disorders such as cancer and Alzheimer-type dementia. To date, evaluation of PKC ligand binding affinity has been performed by competitive studies against radiolabeled probes that are problematic for high-throughput screening. In the present study, we have developed a fluorescent-based binding assay system for identifying ligands that target the PKC ligand binding domain (C1 domain). An environmentally sensitive fluorescent dye (solvatochromic fluorophore), which has been used in multiple applications to assess protein-binding interactions, was inserted in proximity to the binding pocket of a novel PKCδ C1b domain. These resultant fluorescent-labeled δC1b domain analogues underwent a significant change in fluorescent intensity upon ligand binding, and we further demonstrate that the fluorescent δC1b domain analogues can be used to evaluate ligand binding affinity.

How Effective Is Example Generation for Learning Declarative Concepts?

ERIC Educational Resources Information Center

Rawson, Katherine A.; Dunlosky, John

2016-01-01

Declarative concepts (i.e., key terms and corresponding definitions for abstract concepts) represent foundational knowledge that students learn in many content domains. Thus, investigating techniques to enhance concept learning is of critical importance. Various theoretical accounts support the expectation that example generation will serve this…

Universal Design and Outdoor Learning

ERIC Educational Resources Information Center

Harte, Helene Arbouet

2013-01-01

Engagement in the natural environment provides authentic and concrete opportunities for children to enhance development in all domains (Bailie, 2010). As children play and explore in nature they build gross motor development moving through the outdoors. Learning outside and in nature not only allows for learning across subject areas and…

Shaping Solutions from Learnings in PAIs: A Blueprint

ERIC Educational Resources Information Center

Dosanjh, Nawtej; Jha, Pushkar P.

2016-01-01

Purpose: The paper outlines a portal that facilitates learning through sharing of experiences. This flow is between experience sharers and solution seekers in the domain of poverty alleviation interventions (PAIs). Practitioners working on PAIs are often confined to searching from within "lessons learned" repositories and also from…

Robust Fault Diagnosis in Electric Drives Using Machine Learning

DTIC Science & Technology

2004-09-08

detection of fault conditions of the inverter. A machine learning framework is developed to systematically select torque-speed domain operation points...were used to generate various fault condition data for machine learning . The technique is viable for accurate, reliable and fast fault detection in electric drives.

Situated Learning in Young Romanian Roma Successful Learning Biographies

ERIC Educational Resources Information Center

Nistor, Nicolae; Stanciu, Dorin; Vanea, Cornelia; Sasu, Virginia Maria; Dragota, Maria

2014-01-01

European Roma are often associated with social problems and conflicts due to poverty and low formal education. Nevertheless, Roma communities traditionally develop expertise in ethnically specific domains, probably by alternative, informal ways, such as situated learning in communities of practice. Although predictable, empirical evidence of…

Using ELVIS to Measure Experiential Learning in Criminal Justice Internships

ERIC Educational Resources Information Center

Grant, Erin; Dahl, Patricia; Bayens, Gerald

2016-01-01

The purpose of this study is to better understand the relationship between criminal justice internships and knowledge domains. Kolb's four experiential learnings stages of experience, reflection, abstract conceptualization, and active experimentation are assessed using the Experiential Learning Variables and Indicators Scale (ELVIS) to provide a…

Self-Regulated Learning Behaviour in the Finance Industry

ERIC Educational Resources Information Center

Milligan, Colin; Fontana, Rosa Pia; Littlejohn, Allison; Margaryan, Anoush

2015-01-01

Purpose: This paper aims to explore the role of self-regulatory behaviours in predicting workplace learning. As work practices in knowledge-intensive domains become more complex, individual workers must take greater responsibility for their ongoing learning and development. Design/methodology/approach: The study was conducted with knowledge…

Rapid Training of Information Extraction with Local and Global Data Views

DTIC Science & Technology

2012-05-01

relation type extension system based on active learning a relation type extension system based on semi-supervised learning, and a crossdomain...bootstrapping system for domain adaptive named entity extraction. The active learning procedure adopts features extracted at the sentence level as the local

What can management theories offer evidence-based practice? A comparative analysis of measurement tools for organisational context.

PubMed

French, Beverley; Thomas, Lois H; Baker, Paula; Burton, Christopher R; Pennington, Lindsay; Roddam, Hazel

2009-05-19

Given the current emphasis on networks as vehicles for innovation and change in health service delivery, the ability to conceptualize and measure organisational enablers for the social construction of knowledge merits attention. This study aimed to develop a composite tool to measure the organisational context for evidence-based practice (EBP) in healthcare. A structured search of the major healthcare and management databases for measurement tools from four domains: research utilisation (RU), research activity (RA), knowledge management (KM), and organisational learning (OL). Included studies were reports of the development or use of measurement tools that included organisational factors. Tools were appraised for face and content validity, plus development and testing methods. Measurement tool items were extracted, merged across the four domains, and categorised within a constructed framework describing the absorptive and receptive capacities of organisations. Thirty measurement tools were identified and appraised. Eighteen tools from the four domains were selected for item extraction and analysis. The constructed framework consists of seven categories relating to three core organisational attributes of vision, leadership, and a learning culture, and four stages of knowledge need, acquisition of new knowledge, knowledge sharing, and knowledge use. Measurement tools from RA or RU domains had more items relating to the categories of leadership, and acquisition of new knowledge; while tools from KM or learning organisation domains had more items relating to vision, learning culture, knowledge need, and knowledge sharing. There was equal emphasis on knowledge use in the different domains. If the translation of evidence into knowledge is viewed as socially mediated, tools to measure the organisational context of EBP in healthcare could be enhanced by consideration of related concepts from the organisational and management sciences. Comparison of measurement tools across domains suggests that there is scope within EBP for supplementing the current emphasis on human and technical resources to support information uptake and use by individuals. Consideration of measurement tools from the fields of KM and OL shows more content related to social mechanisms to facilitate knowledge recognition, translation, and transfer between individuals and groups.

What can management theories offer evidence-based practice? A comparative analysis of measurement tools for organisational context

PubMed Central

French, Beverley; Thomas, Lois H; Baker, Paula; Burton, Christopher R; Pennington, Lindsay; Roddam, Hazel

2009-01-01

Background Given the current emphasis on networks as vehicles for innovation and change in health service delivery, the ability to conceptualise and measure organisational enablers for the social construction of knowledge merits attention. This study aimed to develop a composite tool to measure the organisational context for evidence-based practice (EBP) in healthcare. Methods A structured search of the major healthcare and management databases for measurement tools from four domains: research utilisation (RU), research activity (RA), knowledge management (KM), and organisational learning (OL). Included studies were reports of the development or use of measurement tools that included organisational factors. Tools were appraised for face and content validity, plus development and testing methods. Measurement tool items were extracted, merged across the four domains, and categorised within a constructed framework describing the absorptive and receptive capacities of organisations. Results Thirty measurement tools were identified and appraised. Eighteen tools from the four domains were selected for item extraction and analysis. The constructed framework consists of seven categories relating to three core organisational attributes of vision, leadership, and a learning culture, and four stages of knowledge need, acquisition of new knowledge, knowledge sharing, and knowledge use. Measurement tools from RA or RU domains had more items relating to the categories of leadership, and acquisition of new knowledge; while tools from KM or learning organisation domains had more items relating to vision, learning culture, knowledge need, and knowledge sharing. There was equal emphasis on knowledge use in the different domains. Conclusion If the translation of evidence into knowledge is viewed as socially mediated, tools to measure the organisational context of EBP in healthcare could be enhanced by consideration of related concepts from the organisational and management sciences. Comparison of measurement tools across domains suggests that there is scope within EBP for supplementing the current emphasis on human and technical resources to support information uptake and use by individuals. Consideration of measurement tools from the fields of KM and OL shows more content related to social mechanisms to facilitate knowledge recognition, translation, and transfer between individuals and groups. PMID:19454008

Augmented reality in medical education?

PubMed

Kamphuis, Carolien; Barsom, Esther; Schijven, Marlies; Christoph, Noor

2014-09-01

Learning in the medical domain is to a large extent workplace learning and involves mastery of complex skills that require performance up to professional standards in the work environment. Since training in this real-life context is not always possible for reasons of safety, costs, or didactics, alternative ways are needed to achieve clinical excellence. Educational technology and more specifically augmented reality (AR) has the potential to offer a highly realistic situated learning experience supportive of complex medical learning and transfer. AR is a technology that adds virtual content to the physical real world, thereby augmenting the perception of reality. Three examples of dedicated AR learning environments for the medical domain are described. Five types of research questions are identified that may guide empirical research into the effects of these learning environments. Up to now, empirical research mainly appears to focus on the development, usability and initial implementation of AR for learning. Limited review results reflect the motivational value of AR, its potential for training psychomotor skills and the capacity to visualize the invisible, possibly leading to enhanced conceptual understanding of complex causality.

A Path Less Chosen: An Assessment of the School of Advanced Military Studies

DTIC Science & Technology

2014-05-22

the theory learned in course one.40 This course used theory , history, doctrine (both US and Soviet), and practical exercises to study the basic...relationships between learning domains, levels of learning and learning objectives, and the experiential learning model.96 In short, there is a major emphasis...discussion. There are multiple theories of education related to the use of discussion in learning . The most frequently cited or referred to amongst

Online selective kernel-based temporal difference learning.

PubMed

Chen, Xingguo; Gao, Yang; Wang, Ruili

2013-12-01

In this paper, an online selective kernel-based temporal difference (OSKTD) learning algorithm is proposed to deal with large scale and/or continuous reinforcement learning problems. OSKTD includes two online procedures: online sparsification and parameter updating for the selective kernel-based value function. A new sparsification method (i.e., a kernel distance-based online sparsification method) is proposed based on selective ensemble learning, which is computationally less complex compared with other sparsification methods. With the proposed sparsification method, the sparsified dictionary of samples is constructed online by checking if a sample needs to be added to the sparsified dictionary. In addition, based on local validity, a selective kernel-based value function is proposed to select the best samples from the sample dictionary for the selective kernel-based value function approximator. The parameters of the selective kernel-based value function are iteratively updated by using the temporal difference (TD) learning algorithm combined with the gradient descent technique. The complexity of the online sparsification procedure in the OSKTD algorithm is O(n). In addition, two typical experiments (Maze and Mountain Car) are used to compare with both traditional and up-to-date O(n) algorithms (GTD, GTD2, and TDC using the kernel-based value function), and the results demonstrate the effectiveness of our proposed algorithm. In the Maze problem, OSKTD converges to an optimal policy and converges faster than both traditional and up-to-date algorithms. In the Mountain Car problem, OSKTD converges, requires less computation time compared with other sparsification methods, gets a better local optima than the traditional algorithms, and converges much faster than the up-to-date algorithms. In addition, OSKTD can reach a competitive ultimate optima compared with the up-to-date algorithms.

Lessons Learned from the Node 1 Atmosphere Control and Storage and Water Recovery and Management Subsystem Design

NASA Technical Reports Server (NTRS)

Williams, David E.

2010-01-01

Node 1 flew to the International Space Station (ISS) on Flight 2A during December 1998. To date the National Aeronautics and Space Administration (NASA) has learned a lot of lessons from this module based on its history of approximately two years of acceptance testing on the ground and currently its twelve years on-orbit. This paper will provide an overview of the ISS Environmental Control and Life Support (ECLS) design of the Node 1 Atmosphere Control and Storage (ACS) and Water Recovery and Management (WRM) subsystems and it will document some of the lessons that have been learned to date for these subsystems based on problems prelaunch, problems encountered on-orbit, and operational problems/concerns. It is hoped that documenting these lessons learned from ISS will help in preventing them in future Programs.

Lessons Learned from the Node 1 Atmosphere Control and Storage and Water Recovery and Management Subsystem Design

NASA Technical Reports Server (NTRS)

Williams, David E.

2011-01-01

Node 1 flew to the International Space Station (ISS) on Flight 2A during December 1998. To date the National Aeronautics and Space Administration (NASA) has learned a lot of lessons from this module based on its history of approximately two years of acceptance testing on the ground and currently its twelve years on-orbit. This paper will provide an overview of the ISS Environmental Control and Life Support (ECLS) design of the Node 1 Atmosphere Control and Storage (ACS) and Water Recovery and Management (WRM) subsystems and it will document some of the lessons that have been learned to date for these subsystems based on problems prelaunch, problems encountered on-orbit, and operational problems/concerns. It is hoped that documenting these lessons learned from ISS will help in preventing them in future Programs.

76 FR 76393 - Notice of Proposed Information Collection Requests

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-07

..., including through the use of information technology. Dated: December 2, 2011. Darrin King, Director... Collection: 21st Century Community Learning Centers: Lessons Learned Guides. OMB Control Number: 1875--NEW... Community Learning Centers (21st CCLC) program that will assist the U.S. Department of Education staff in...

Human Learning and Memory

ERIC Educational Resources Information Center

Lieberman, David A.

2012-01-01

This innovative textbook is the first to integrate learning and memory, behaviour, and cognition. It focuses on fascinating human research in both memory and learning (while also bringing in important animal studies) and brings the reader up to date with the latest developments in the subject. Students are encouraged to think critically: key…

PERSO: Towards an Adaptive e-Learning System

ERIC Educational Resources Information Center

Chorfi, Henda; Jemni, Mohamed

2004-01-01

In today's information technology society, members are increasingly required to be up to date on new technologies, particularly for computers, regardless of their background social situation. In this context, our aim is to design and develop an adaptive hypermedia e-learning system, called PERSO (PERSOnalizing e-learning system), where learners…

26 CFR 1.25A-0 - Table of contents.

Code of Federal Regulations, 2011 CFR

2011-04-01

... Credit and Lifetime Learning Credit. (1) In general. (2) Hope Scholarship Credit. (3) Lifetime Learning... conviction. (2) Examples. (e) Academic period for prepayments. (1) In general. (2) Example. (f) Effective date. § 1.25A-4Lifetime Learning Credit (a) Amount of the credit. (1) Taxable years beginning before...

26 CFR 1.25A-0 - Table of contents.

Code of Federal Regulations, 2013 CFR

2013-04-01

... Credit and Lifetime Learning Credit. (1) In general. (2) Hope Scholarship Credit. (3) Lifetime Learning... conviction. (2) Examples. (e) Academic period for prepayments. (1) In general. (2) Example. (f) Effective date. § 1.25A-4Lifetime Learning Credit (a) Amount of the credit. (1) Taxable years beginning before...

26 CFR 1.25A-0 - Table of contents.

Code of Federal Regulations, 2012 CFR

2012-04-01

... Credit and Lifetime Learning Credit. (1) In general. (2) Hope Scholarship Credit. (3) Lifetime Learning... conviction. (2) Examples. (e) Academic period for prepayments. (1) In general. (2) Example. (f) Effective date. § 1.25A-4Lifetime Learning Credit (a) Amount of the credit. (1) Taxable years beginning before...

26 CFR 1.25A-0 - Table of contents.

Code of Federal Regulations, 2014 CFR

2014-04-01

... Credit and Lifetime Learning Credit. (1) In general. (2) Hope Scholarship Credit. (3) Lifetime Learning... conviction. (2) Examples. (e) Academic period for prepayments. (1) In general. (2) Example. (f) Effective date. § 1.25A-4Lifetime Learning Credit (a) Amount of the credit. (1) Taxable years beginning before...

The Complete Learning Disabilities Directory. 2017 Edition

ERIC Educational Resources Information Center

Grey House Publishing, 2016

2016-01-01

Published for over a decade, this directory continues to be a successful, sought-after resource, providing valuable information to professionals, families, and individuals in the learning disabilities community. Supported by the National Center for Learning Disabilities, this 2017 edition brings together the most up-to-date information on LD…

The Complete Learning Disabilities Directory. 2011 Edition

ERIC Educational Resources Information Center

Grey House Publishing, 2010

2010-01-01

Published for over a decade, this directory continues to be a successful, sought-after resource, providing valuable information to professionals, families, and individuals in the learning disabilities community. Supported by the National Center for Learning Disabilities, this 2011 edition brings together the most up-to-date information on LD…

26 CFR 1.1445-4 - Liability of agents.

Code of Federal Regulations, 2011 CFR

2011-04-01

... soon as possible after learning of the false certification or statement, but not later than the date of the transfer (prior to the transferee's payment of consideration). If an agent first learns of a false... a non-U.S. real property interest statement) in connection with that transaction. I have learned...

26 CFR 1.1445-4 - Liability of agents.

Code of Federal Regulations, 2010 CFR

2010-04-01

... after learning of the false certification or statement, but not later than the date of the transfer (prior to the transferee's payment of consideration). If an agent first learns of a false certification... a non-U.S. real property interest statement) in connection with that transaction. I have learned...

Implications of Bishop Tuff zircon U-Pb ages for rates of zircon growth and magma accumulation

NASA Astrophysics Data System (ADS)

Reid, M. R.; Schmitt, A. K.

2012-12-01

Rates of geologic processes obtained from natural studies rely on accurate geochronologic information. An important benchmark in geochronology as well as a valuable source of insights into the evolution of voluminous explosive eruptions is the >600 km3 Bishop Tuff (BT). A recently determined weighted mean 206Pb/238U date of 767.1±0.9 ka for a BT zircon population [1] is indistinguishable from the recalibrated 40Ar/39Ar sanidine date of 767.4±2.2 ka [2], potentially providing a key intercalibration point between astronomical and radio-isotopic dating approaches. Consequences of these results are linear zircon growth rates of >1×10-14 cm/sec and magma accumulation rates of >200 km3/ka. In contrast, spatially selective SIMS U-Pb dating of BT zircons yielded mean pre-eruption ages of 850 ka [3], a difference that raises questions about the validity of intercalibration between U-Pb and K-Ar dating methods and the history of magma accumulation. We obtained new SIMS analyses of the BT zircons using more spatially and analytically sensitive methods and verifying our accuracy against the TIMS dated Quaternary zircon 61.308A (2.488±0.002 Ma). Analyses were performed on zircon rims and on oriented cross-sections exposed during optical interferometry-calibrated serial sectioning removing the outermost ~31 μm. Sputtering by a 100 nA ion beam versus the normally employed 10-12 nA beam resulted in enhanced radiogenic Pb yields and analytical uncertainties for Quaternary zircon approaching the U-Pb age reproducibility of the primary zircon standard (~1-2 % for AS3). Ages obtained at ~31 μm depth (representing <5% of crystal growth in most cases) average 892±26ka (MSWD=0.29), corroborating previous evidence for residence times of several tens of ka. Rim ages average 781±22 ka (MSWD=0.61), overlapping Ar/Ar determinations of eruption age and corroborating the importance of near-eruption aged zircon growth. Our results confirm the presence of BT zircon domains that predate eruption by tens of ka, domains that could be difficult to detect by single crystal analyses. SIMS analyses can selectively sample more interior portions of grains whereas whole grain TIMS analyses will be volumetrically biased towards the outermost ~20% of the BT zircons. Spots centered on BT zircon cores sample a domain representing only a few volume percent of the crystal; if mantled completely by eruption-aged growth, single crystal zircon ages are predicted to be <5 ka older than eruption, extrapolating from the SIMS dates. When, compared to grain interiors, the greater average near-rim U concentrations are factored into this mass balance, the influence of these older domains is further diminished. A scenario that can at least partially reconcile the disparate zircon dates in the context of evolution of the BT and the dynamics of zircon crystallization is as follows: (1) zircon nucleation and relatively rapid growth an average of ~100 ka before eruption; (2) significant decay in zircon growth rates as temperatures and Zr melt gradients relax; and, finally, (3) mantling of earlier zircon cores by rejuvenation and renewed BT zircon growth during the lead-up to eruption. Comparisons between spot and single grain dating show that most zircon growth likely occurred close to eruption. [1] Crowley et al., 2007.Geology 35, 1123. [2] Rivera et al., 2011. Earth Planet. Sci. Lett. 311, 420. [3] Simon and Reid, 2005. Earth Planet. Sci. Lett. 235, 123.